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[Assistant] Real part, plus and minus some imaginary part. Then we want the real part to be negative. Real part of lambda, which is A, should be zero. So that's our requirement.


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[Assistant] And we, the real part should be zero so that e to the, the point about this negative a was that e to the a t will go to zero.


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[Assistant] The point about these negative lambdas is that e to the lambda t will go to zero. This is stability. So my question is, what's the test on the matrix that decides this about the eigenvalues?


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[Assistant] What do we, what do we, can we look at the matrix?


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[Assistant] Maybe we don't have to find those eigenvalues.


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[Assistant] Maybe we can use the fact. Again, the fact is that lambda 1 plus lambda 2 is the trace.


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[Assistant] And lambda 1 times lambda 2 is the determinant. And we can read those numbers off from the matrix.


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[Assistant] Then there's a quadratic equation, but if we only want to know


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[Assistant] Information like, are the eigenvalues negative? Are their real parts negative?


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[Assistant] Finding the eigenvalues from that quadratic equation. Wouldn't be that hard to do, but we don't have to do it. Okay, so suppose we have two negative eigenvalues. Then certainly, this would mean the trace would be negative.


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[Assistant] Because the trace is the sum of the eigenvalues. If those are both negative, trace is negative.


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[Assistant] So we can check about the trace just right away. What about the determinant? If that's negative and that's negative,


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[Assistant] Then the multiplying those will give a positive number, so the determinant should be positive. So trace less than 0, determinant greater than 0. That is the stability test. That's the stability test.


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[Assistant] The 2x2 matrix ABCD, if its trace is negative and its determinant is positive, is stable. That's the test.


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[Assistant] And actually, it works also if lambda comes out complex, because lambda 1 plus lambda 2


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[Assistant] And we want that to be negative. So again, trace negative.


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[Assistant] Trace negative, even if the roots are real, or if they're complex, that still tells us that the sum of the roots is negative, and the determinant also works.


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[Assistant] And I can apply it to a few matrices. I wrote down a few matrices. Uh, can I just?


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[Assistant] Look at that test. Can you look at that test and just apply it to see, uh,


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[Assistant] So here's an example, say, minus 2,


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[Assistant] Minus one, three, and four. Is that any good?


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[Assistant] The trace is minus 3, that's good. The determinant is 2, minus 12, minus 10, that's bad.


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[Assistant] That's bad. So I better, if I, so that would be unstable. The determinant


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[Assistant] That has a negative determinant, unstable. So I'll put an x through that. Unstable. Let me take a stable one.


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[Assistant] The stable one I'm going to want like minus five and one. Let's say that's okay. The trace is negative, minus four. And now I want to keep, make the determinant positive. So maybe I better put like six and minus seven.


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[Assistant] And the determinant test is passed. So that is okay. That one would be stable.


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[Assistant] The matrix, if, if this was my matrix A, then the


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[Assistant] Solutions to dy dt equal ay, y prime equal ay is my differential equation.


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[Assistant] The two solutions which would track the eigenvectors would have negative lambdas.


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[Assistant] Negative lambdas, because the trace is negative and the determinant is positive, passes the stability test and the solutions would go to minus infinity. Okay, that's two by twos. Thank you.


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[Assistant] How do you remember all that? I don't have to remember it. The moon's right there. What's that doing here? It's daytime. I don't know, but it sure makes it easier to draw. Wait till we tell Quack. He's gonna be so surprised.


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[Assistant] Asking a beaver is not scientific.


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[Assistant] Well, I can't show you proof. No.


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[Assistant] He said you would travel past our abbey someday. Please, come in.


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[Assistant] Our master is the great immortal, said the first priest. He is very wise and powerful.


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[Assistant] Our master is visiting friends in heaven right now.


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[Assistant] If he wasn't powerful, he wouldn't be able to do that.


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[Assistant] Its fruit takes ten thousand years to become ripe.


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[Assistant] According to legend one bite of the fruit will make you live forever. Would you like one?


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[Assistant] It's not a baby, said one priest. It's a ginseng fruit. It only looks like a baby to you because you're immortal.


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[Assistant] Journey to the West, Chapter 23, Great Protectors.


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[Assistant] He lunged at the monkey again Wukong jumped out of the way


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[Assistant] Said the pig. He swung his rake again.


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[Assistant] As they traveled, the pig kept complaining.


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[Assistant] They went around a bend and saw a large tiger.


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[Assistant] Bajie and Wukong quickly pulled out their weapons.


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[Assistant] Said the tiger. He looked at the tang monk.


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[Assistant] The tiger showed his claws. Then he lunged at Bajie.


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[Assistant] The pig hit him with the rake. The tiger tumbled over. Wukong ran toward the tiger with his iron bar.


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[Assistant] The tiger dodged the bar and then almost got hit by the rake again. He turned and fled. Wukong and Bajie ran after the tiger.


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[Assistant] Then, they spotted a flash of orange behind some bushes.


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[Assistant] Whispered Bajie. The monkey and pig sneaked up to the bushes. But the tiger wasn't there.


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[Assistant] Instead, a tiger's skin lay over a rock.


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[Assistant] I can sit on that frying pan all day and not get hurt at all. But the Tang monk is mortal. He'll be burned to a crisp!


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[Assistant] Chirp and Quack knew they had to help Peep. Because that's what friends do.


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[Assistant] Band 6, Part 2, Listening comprehension. Section A, Directions.


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[Assistant] In this section you will hear two long conversations. At the end of each conversation you will hear four questions.


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[Assistant] Both the conversation and the questions will be spoken only once.


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[Assistant] After you hear a question, you must choose the best answer from the four choices marked A, B, C, and D. Then mark the corresponding letter on answer sheet 1 with the single line through the center.


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[Assistant] Do you mind taking my photo with the statue over there? I think it will make a great shot.


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[Assistant] My dream is to become an online celebrity of sorts.


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[Assistant] I just got the idea a few months ago after posting some holiday photos on my social media accounts.


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[Assistant] A lot of people liked my photos and started asking me for travel tips. So I figured I'd give it a go.


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[Assistant] I post a lot on social media anyway, so I've got nothing to lose.


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[Assistant] Recently, I've been spending a lot more time editing photos, posting online, and clearing storage on my phone. It's always full now. That doesn't sound like too much work. Well there's more to it.


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[Assistant] I spent all last weekend researching what topics are popular.


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[Assistant] What words to use in captions and similar accounts to follow. It really was a lot to take in, and I was up well past midnight. I'd say it's paying off though.


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[Assistant] I increased the number of people following my accounts by 15% already.


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[Assistant] Here we interview some of the greatest minds in physics as they help us to understand some of the most complicated theories.


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[Assistant] Today, I'm very pleased to welcome Dr. Melissa Phillips, Professor of Theoretical Physics. She's here to tell us a little about what it is she studies. Dr. Phillips, you seem to study everything.


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[Assistant] That's because matter and antimatter are basically opposites of each other.


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[Assistant] They are exactly alike except that they have opposite electrical charges. So when they collide, they destroy each other?


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[Assistant] But a recent study seems to point to the fact that when matter and antimatter were first created, there were slightly more particles of matter, which allowed the universe we all live in to form.


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[Assistant] Questions 5 to 8 are based on the conversation you have just heard.


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[Assistant] In this week's edition of Special Series on Bizarre Medical Conditions, there's a report of the case of Michelle Myers.


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[Assistant] Myers is an American woman who woke up one day speaking with a British accent.


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[Assistant] Her British accent has remained for the past two years.


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[Assistant] However, on both of those occasions the accents lasted for only a week.


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[Assistant] Myers has been diagnosed with foreign accent syndrome.


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[Assistant] It's a disorder in which a person experiences a sudden change to their speech so that they sound like they are speaking in a foreign accent.


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[Assistant] The condition is most often caused by a stroke or traumatic brain injury.


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[Assistant] Although people with the syndrome have intelligible speech.


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[Assistant] Their manner of speaking is altered in terms of timing and tongue placement, which may distort their pronunciation.


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[Assistant] The result is that they may sound foreign when speaking their native language.


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[Assistant] It's not clear whether Myers has experienced a stroke or other brain damage.


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[Assistant] But she also has a separate medical condition which can result in loose joints, easily bruised skin, and other problems.


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[Assistant] Thorn Accent Syndrome is rare, with only about 60 cases reported within the past century.


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[Assistant] However, a different American woman reportedly spoke with a Russian accent in 2010 after she fell down the stairs and hit her head.


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[Assistant] Questions 12 to 15 are based on the passage you have just heard.


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[Assistant] Today I'm going to talk about a very special kind of person.


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[Assistant] Psychologists call them masters of deception.


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[Assistant] Those rare individuals with the natural ability to tell with complete confidence when someone is telling a lie.


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[Assistant] For decades, researchers and law enforcement agencies have tried to build a machine that will do the same thing.


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[Assistant] Now, a company in Massachusetts says that by using magnetic brain scans, they can determine with 97% accuracy whether someone is telling the truth.


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[Assistant] They hope that the technology will be cleared for use in American courts by early next year.


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[Assistant] But is this really the ultimate tool for you, the lawyers of tomorrow?


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[Assistant] You will not find many brain scientists celebrating this breakthrough. The company might be very optimistic.


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[Assistant] That's because the technology has not been properly tested in real world situations. In life,


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[Assistant] There are different kinds of lies and diverse contexts in which they're told.


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[Assistant] These differences may elicit different brain responses.


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[Assistant] Does their hypothesis behind the test apply in every case?


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[Assistant] We don't know the answer because studies done on how reliable this machine is have not yet been duplicated. Much more research is badly needed.


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[Assistant] Whether the technology is eventually deemed reliable enough for the courts will ultimately be decided by the judges.


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[Assistant] Let's hope they're wise enough not to be fooled by a machine that claims to determine truthfulness at the flip of a switch.


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[Assistant] They should also be skeptical of the growing tendency to try to reduce all human traits and actions to the level of brain activity. Often, they do not map that easily.


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[Assistant] Understanding the brain is not the same as understanding the mind.


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[Assistant] Some researchers have suggested that thoughts cannot properly be seen as purely internal. Instead,


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[Assistant] Thoughts make sense only in reference to the individual's external world.


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[Assistant] So while there may be insights to be gained from matching behavior to brain activity,


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[Assistant] Those insights will not necessarily lead to justice in a court of law.


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[Assistant] Problems surround the use of machines to spot deception, at least until it has been rigorously tested.


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[Assistant] A high tech test that can tell when a person is not telling the truth sounds too good to be true. And when something sounds too good to be true, it usually is.


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[Assistant] What have the diverse team of researchers found about the previous studies on language diversity?


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[Assistant] We often hear people say that America is a land of opportunity, a country built on hope to aspire to greatness, on the American dream. But is the dream as we once knew it dying?


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[Assistant] The question is, what is it going to take to change things? Maybe one day soon, real change will actually be made in our nation and the gap will be eradicated. But what happens in the meantime? Is there something that we can do to help close the gap?


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[Assistant] It is a grim reality that you can have one person who only makes around $13,000 a year, while across town, another is making millions. For me, it is kind of astonishing. And if you ask low-income people what's the one thing that would change their life, they'll say a full-time job. That's all they aspire to.


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[Assistant] So why is it so difficult for so many people to find employment?


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[Assistant] It partly comes down to profit driven business models that are built around low wage work and part time jobs that don't provide benefits. Businesses in order to bolster profits.


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[Assistant] hire employees as part-time workers only.


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[Assistant] This means they are paid the lowest legal wage and receive no healthcare or other benefits provided to full-time employees. Simultaneously, technological advancement


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[Assistant] And a global economy has reduced the demand for well-paid blue collar jobs here in the United States.


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[Assistant] The cumulative effect of these two factors is that many Americans are forced to take two or more part-time jobs just to make ends meet.


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[Assistant] What has become obvious to me when it comes to the income gap?


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[Assistant] Is that there needs to be an opportunity for the people at the bottom to push them back up.


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[Assistant] And push them into the middle class to give them hope in their lives.


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[Assistant] Question 3. What has the man been busy doing recently?


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[Assistant] Question 4. What does the woman say about her photos?


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[Assistant] What is the woman physicist's main research area?


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[Assistant] Question 7. What is the woman interested in?


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[Assistant] Question 8. What seems to be the finding of the recent study?


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[Assistant] Question 13. What did Jenny Landroth do recently?


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[Assistant] Question 14. What do we learn about women in the Victorian era?


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[Assistant] Question 15. What does the passage say about Gertrude Ederle?


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[Assistant] Question 20. What do we learn from the talk about languages in the world?


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[Assistant] What does Dana say about the interpreters she knows?


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[Assistant] What do most interpreters think of consecutive interpreting?


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[Assistant] For what purpose does Fred Nowuski appeal for more funding?


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[Assistant] What does Cambridge scientist Peter Wadhams say in his study?


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[Assistant] Question 22. How does Peter Wadhams view climate change?


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[Assistant] In this next module we're going to talk about the writing step. This is the step where you're writing the first draft of your piece. As I've said, this is the hardest step for most people.


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[Assistant] This is where you have to pop open that blank word document and start writing.


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[Assistant] Or, hopefully, you're popping open some kind of a roadmap so that you have something to start with.


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[Assistant] My biggest tip for the first draft is don't be a perfectionist. A lot of scientists are perfectionists and they want to get it right on the first try. But writing the first draft is not the place to be a perfectionist.


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[Assistant] My only goal when writing the first draft is to get down my ideas in complete sentences and in order. That's it. The sentences don't have to sound good, they just have to be grammatically complete and in the right place.


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[Assistant] I purposely set a low bar so that I can get through the first draft quickly.


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[Assistant] In the first draft, you want to focus on the high level ideas, the take home messages, and the logical organization. Don't worry about the sentence level details.


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[Assistant] It's much easier to fix the sentence level details during revision than it is to fix things like the logical organization.


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[Assistant] If your logical organization is off and your take home messages are muddled, you end up having to revise the whole piece and that revision process is so much harder. Sentence level editing, that's relatively easy.


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[Assistant] So just get the ideas down in complete sentences and don't worry about what the sentences sound like.


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[Assistant] The other argument for writing the first draft quickly is it's the hardest step for most people. Minimize the pain by writing your first draft quickly and efficiently.


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[Assistant] I know that the editing and the elegance in the writing can happen on revision.


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[Assistant] This may be a different approach to writing than you are used to, but try it. It will make your writing life so much easier.


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[Assistant] Errors in publication occur when the authors have typos, omissions, or such poor writing of the methods that others cannot figure out what they did or reproduce their tables and figures. Sometimes there's just too much to write up that errors will occur in almost every case. Notice that these sentences are clunky.


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[Assistant] I've got a boring verb have in the first sentence. In the second sentence, I've used an unnecessary there is, which is something I've told you not to do.


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[Assistant] I got in all the details that I wanted to get across, and I did hold myself to complete sentences.


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[Assistant] That was the first draft. Now let me show you my revised version.


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[Assistant] It says published papers frequently have typos, omissions, and otherwise poor documentation of methods.


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[Assistant] These errors make it impossible to figure out exactly what was done or to reproduce the results.


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[Assistant] So you can see that this paragraph very much resembles the first draft, except it's more clear and concise and elegant. It's more to the point.


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[Assistant] Here's another example from my own writing. This was from the first draft of a story that was about the fact that modern humans seem to have some archaic genes, some neanderthal genes, in their DNA.


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[Assistant] This paragraph speculates about some potential practical implications of harboring those genes.


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[Assistant] A potential implication is, notice my boring to be verb here, is that people who carry archaic HLAs could be more prone to autoimmunity.


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[Assistant] Autoimmunity is associated with HLA factors. There could be downsides to archaic HLAs.


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[Assistant] This is very boring writing. Since we've evolved separately from Neanderthals, notice my typo there, for a few hundred thousand years, we may have evolved important differences in the proteins that interact with HLA. The archaic HLAs may interact more poorly with some of these proteins, potentially causing mistakes like autoimmunity, and then I've got a quote at the end.


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[Assistant] Uh, Parim says this is all just speculation, but we have been apart for all this time, so it would be very surprising if there weren't differences, Parim says, it would solve a long-standing puzzle. Notice.


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[Assistant] That I managed to squeeze in all the ideas that I wanted to make into this paragraph. But some of the writing is not very good. I have a lot of boring verbs, boring sentence structure.


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[Assistant] But all the main ideas are there and in complete sentences, and it didn't take me long to write.


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[Assistant] Neanderthal or Denisovan proteins continue to live on and function inside us, and this may also have a downside parhamnids.


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[Assistant] Neanderthals evolved separately from us for a few hundred thousand years, so their proteins may be somewhat mismatched to our immune systems and could play a role in autoimmune disease. Autoimmunity is poorly understood but known to be related to HLA types, and then we get the quote.


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[Assistant] Notice this paragraph has all the same ideas as the original, but it's much more succinct and clear and elegant.


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[Assistant] But it didn't start that way. My first draft was rather messy.


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[Assistant] It evolved into this through revision, through me editing my own work.


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[Assistant] Alright, one more example. This was a paragraph from the lead of a story I was writing. Here's the first draft.


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[Assistant] It says, it's also difficult to study the biology because the brain is so inaccessible.


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[Assistant] Cancer scientists can take out a tumor and look directly at the cells, but autism researchers cannot directly study brain cells except on autopsy, let alone developing brain cells.


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[Assistant] Stanford is on the cutting edge of solving this problem. In fact, Del Melch's solution is so innovative it seems straight out of a science fiction novel.


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[Assistant] I got that little cute thing about science, the science fiction novel in at the end. This isn't bad, it has some nice parts to it, but it's not great. I've got boring verbs, it's a little wordy, I'm starting with an it is. That was my first draft, and then I went back and revised it.


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[Assistant] My revision says it's also difficult to access the brain. Scientists can slice cancer cells out of a tumor and directly study them, but they can't just scoop cells out of the brain, let alone the developing brain.


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[Assistant] Notice that I added some great verbs in there, slice and scoop, and I've cut some extra words so it's more succinct.


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[Assistant] That was the version I sent to my editor, but then my editor revised it even a little bit more. Here's the revised version that actually got printed.


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[Assistant] Scientists can slice cancer cells out of a tumor and study them directly, but they can't just scoop cells out of the brain.


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[Assistant] Stanford is on the forefront of solving this problem. In fact, Dometch's solution seems straight out of a science fiction novel.


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[Assistant] You can see that this is even more clear and even more elegant.


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[Assistant] This went through multiple rounds of revision to get this way. It didn't start that way.


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[Assistant] So it's okay on a first draft to violate some of the rules I've been talking about for good writing. You can fix all of that later.


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[Assistant] As long as your ideas are clearly laid out and you know what you want to go in each paragraph, that sentence level editing, that can happen after you've written the first draft. That can happen during revision.


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[Assistant] In this section you will hear two long conversations. At the end of each conversation you will hear four questions.


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[Assistant] Both the conversation and the questions will be spoken only once.


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[Assistant] After you hear a question, you must choose the best answer from the four choices marked A, B, C, and D.


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[Assistant] Then mark the corresponding letter on answer sheet 1 with a single line through the center.


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[Assistant] Hey, I just read a great book about physics. I think you'd like it. It's called The Physics of the World. It's written by a scientist named Silvia Mendez.


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[Assistant] And it's refreshing to see a strong, curious, clever woman adding her voice to the scientific discourse in a field that has been traditionally dominated by men.


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[Assistant] I think she is to be commended for making an effort to include anecdotes about little known female scientists.


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[Assistant] You know, they were often victims of a generation firmly convinced that the woman's place was in the home.


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[Assistant] Yeah, I like how she cultivates scientific engagement by providing a host of do-it-yourself experiments that bring the same foundational principles of classical physics that govern everything from the solar system to your kitchen table.


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[Assistant] From using complex laws of physics to test whether a spinning egg is cooked.


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[Assistant] To measuring atmospheric pressure by lifting a piece of cardboard.


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[Assistant] Her hands-on examples make her book a truly interactive read.


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[Assistant] Questions 1 to 4 are based on the conversation you have just heard. Question 1 What does the woman say about the book the man recommended?


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[Assistant] Question 2. What can we find in the books a man recommended?


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[Assistant] Question 3. How does the author bring her book to life?


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[Assistant] How does the book cultivate readers' interest in physics?


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[Assistant] I was hoping I could have a moment of your time if you're not too busy.


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[Assistant] I'm having some problems getting started on my dissertation, and I was hoping you could give me some advice on how to begin.


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[Assistant] The general topic I chose is aesthetics, but that's as far as I've got. I don't really know where to go from there.


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[Assistant] I was hoping it would be possible for me to change topics. I'm really more interested in nature than beauty.


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[Assistant] Oh yeaah. He's the philosopher who wrote about where our ideas of beauty come from.


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[Assistant] Great. Thanks for taking the time to answer my questions, Professor. I'll let you get back to class now.


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[Assistant] Questions 5 to 8 are based on the conversation you have just heard. Question 5. What is the man's problem?


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[Assistant] Question 6. What does the professor think of the man's topic?


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[Assistant] Question 7. What is the man really more interested in?


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[Assistant] Question 8. What does the professor say the man has to do?


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[Assistant] Questions 9 to 11 are based on the passage you have just heard. Question 9. What did climate scientists describe as stunning?


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[Assistant] What does the passage say about the temperature surge in the Arctic?


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[Assistant] What may occur in 20 years according to scientists' recent observations?


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[Assistant] A good dose of willpower is often necessary to see any task through.


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[Assistant] Whether it's sticking to a spending plan or finishing a great novel.


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[Assistant] And if you want to increase that willpower, a new study suggests you just simply have to believe you have it. According to this study, what matters most is what we think about our willpower.


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[Assistant] If we believe it's a finite resource, we act that way.


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[Assistant] We feel exhausted and need breaks between demanding mental tasks. However


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[Assistant] People who view their willpower as a limitless resource get energized instead.


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[Assistant] The researchers used a psychological assessment tool to test the validity of the study.


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[Assistant] They asked 1,100 Americans and 1,600 Europeans to grade different statements such as


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[Assistant] I can focus on a mental task for long periods without feeling tired.


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[Assistant] Although there was little difference between men and women overall.


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[Assistant] Americans were more likely to admit to needing breaks after completing mentally challenging tasks. European participants, on the other hand, claimed they were able to keep going.


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[Assistant] Based on the findings, the researchers suggest that the key to boosting your willpower is to believe that you have an abundant supply of it. Your feelings about your willpower affect the way you behave. But these feelings are changeable, they said.


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[Assistant] Changing your beliefs about the nature of your self-control can have positive effects on character development.


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[Assistant] This leads to healthier behaviors and perceptions of other people.


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[Assistant] Questions 16 to 18 are based on the recording you have just heard. Question 16.


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[Assistant] What did the researchers at Oxford University conclude?


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[Assistant] What do we learn about Kaggle Company's winning programs?


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[Assistant] We've talked recently about the importance of sustainable energy.


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[Assistant] We've also talked about the different theories on how that can be done. So far, our discussions have all been theoretical. Now, I have a practical question for you all.


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[Assistant] Can you run a 140,000 kilogram train on just the steam generated by solar power?


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[Assistant] Well, one engineer, Tim Kasselman, believes it's possible.


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[Assistant] And his home city of Sacramento, California should see the technology's first test.


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[Assistant] As part of the upgrading of its railyard, Castleman, who is an inventor and self-proclaimed steam visionary,


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[Assistant] Is campaigning for a new steam train that runs without any fire and could run on an existing 10 kilometer line.


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[Assistant] Drawing tourists and perhaps offering city commuters a green alternative to their cars.


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[Assistant] Castleman wants to build an array of solar magnifying mirrors at one end of the line to collect and focus heat onto water-filled tubes.


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[Assistant] This would generate steam that could be used to fill tanks on a small steam train without the use of fire.


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[Assistant] Supplying power to trains in this way would offer the shortest distance from well to wheels, he says, with the least amount of energy lost.


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[Assistant] According to Harry Valentin, a Canadian engineer who is researching modern steam technology,


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[Assistant] A special tank measuring 2 by 10 meters could store over 750 kilowatt hours of energy as high pressure steam.


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[Assistant] Enough to pull a two car train for an hour or so.


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[Assistant] Energy to drive a steam locomotive can be stored in other materials besides water.


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[Assistant] For example, a team at Tohoku University in Japan has studied materials that can store large amounts of heat. When heated, these materials turn from a solid into a liquid, absorbing energy as they change phase.


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[Assistant] The liquid is maintained above its melting point until steam is required.


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[Assistant] Has tested calcium compound as an energy storage material.


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[Assistant] Heating this chemical compound dries off carbon dioxide gas, leaving calcium oxide. The gas can be stored under pressure in a tank. To recover the energy, the gas is fed back over the calcium oxide. In theory, says Valentin,


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[Assistant] This can create a high enough temperature to generate superheated steam.


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[Assistant] Questions 22 to 25 are based on the recording you have just heard. Question 22.


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[Assistant] What is one cause of the current crisis in care for the elderly in England?


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[Assistant] What does the speaker say about residential and community care?


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[Assistant] What made management of care for the elderly more difficult in the 1980s?


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[Assistant] Question 25. What does the speaker say about older people in England?


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[Assistant] Okay Wukong, I will give you until the end of the day to fix my ginseng tree.


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[Assistant] If you can't, the Tang Monk goes into the frying pan.


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[Assistant] I would like to share some ginseng fruit with everyone here.


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[Assistant] The Secret Garden, Chapter 4, The Housemaid.


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[Assistant] The next morning Mary woke up when a young housemaid came into her room.


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[Assistant] While the young maid cleaned up the cinders in the fireplace, Mary lay in bed and looked around the gloomy room.


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[Assistant] The walls were covered with strange tapestries embroidered with forest scenes. Through a window she could see a great stretch of land


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[Assistant] It looked like an endless, dull purple sea.


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[Assistant] As the maid lit the fire, Mary listened to her with a puzzled expression.


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[Assistant] Her nanny and the others did not talk to their masters in such a friendly way.


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[Assistant] Demanded Mary. Martha looked at Mary in amazement.


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[Assistant] Then they went into the next room where she set out Mary's breakfast on a table.


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[Assistant] She was amazed at how the servant talked on and on.


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[Assistant] Mary had never had a pet of her own, but she'd always wanted one. She began to be a little interested in Dickon. This was something new.


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[Assistant] The only person she'd ever been interested in before was herself.


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[Assistant] She drank some tea and ate some toast with marmalade.


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[Assistant] She saw gardens and paths and big trees, but everything looked dull and wintry.


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[Assistant] It was this mention of Dickon that made Mary decide to go out, though she was not aware of it. Perhaps she would see some birds.


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[Assistant] They would be different from those in India and it might amuse her to look at them. Martha found Mary's coat and hat for her.


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[Assistant] Then Martha showed Mary the way downstairs and outside.


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[Assistant] She said, pointing to a gate in a wall of shrubbery.


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[Assistant] And with that, Martha was off, leaving Mary to wander outside by herself.


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[Assistant] And as that head priest tried to do, they might harm the Tang monk.


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[Assistant] You don't belong in the Jade Palace. You're a disgrace to Kung Fu, and if you have any respect for who we are and what we do, you will be gone by morning.


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[Assistant] What do we do now, Master? With the Panda gone, who will be the Dragon Warrior?


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[Assistant] Down in the jungle, come if you dare. What can you see shaking here and there? With a shaky shake here and a shaky shake there. What's that creature shaking here and there? It's a bear!


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[Assistant] Boogie woogie woogie, shake, shake. Boogie woogie woogie, that's the way she's shaking here and there.


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[Assistant] Down in the jungle where nobody sees What can you see swinging through the trees With a swingy swing here and a swingy swing there What's that creature swinging through the trees? It's a monkey!


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[Assistant] Down in the jungle in the midday heat What can you see stomping its feet? With a stompy stomp here and a stompy stomp there What's that creature stomping its feet? It's an ELEPHANT!


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[Assistant] She goes stomp, stomp, boogie, woogie, oogie. Stomp, stomp, boogie, woogie, oogie. Stomp, stomp, boogie, woogie, oogie. That's the way she's stomping her feet.


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[Assistant] Down in the jungle where the trees grow high What can you see flying in the sky? With a flappy flap here and a flappy flap there What's the creature flying in the sky? It's a bird!


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[Assistant] Down in the jungle where the leaves lie deep What can you see learning how to leap? With a leapy leap here and a leapy leap there What's that creature learning how to leap? It's a leopard!


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[Assistant] Down in the jungle where the stars are shining bright Who can you see swaying left and right With a sway sway here and a sway sway there Who's swaying left and swaying right? We are!


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[Assistant] What do we learn about the goods sold at the woman's shop?


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[Assistant] Why doesn't the woman want to make known their earnings anymore?


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[Assistant] What does the speaker say about the seabirds called fulmas?


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[Assistant] What did scientists previously notice about pollutants in the Arctic?


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[Assistant] What does the speaker warn about at the end of the talk?


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[Assistant] What do professional social workers have in common?


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[Assistant] What is Mel Wilson going to talk about in the series?


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[Assistant] We aren't doodle folk. Wrath runs deep through our veins.


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[Assistant] I think it's time I told you something I should have told you a long time ago.


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[Assistant] That's the good rich earth, he said, digging away.


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[Assistant] The sun's warming them. You'll see bits of green sticking up soon.


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[Assistant] Crocuses and snowdrops and daffodils. Haven't you ever seen them?


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[Assistant] You'll have to wait for them. They'll poke up a bit higher here and push out a bit more there.


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[Assistant] Then they'll uncurl a leaf this day and another one that day. You watch.


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[Assistant] Remember you, said Ben. Of course he does.


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[Assistant] Ask the robin. He's the only one who knows. No one else has seen it for ten years.


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[Assistant] College English Test Band 6, Part 2, Listening Comprehension.


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[Assistant] Hello everybody, I am happy to introduce our admirable speaker for today's lecture, Dr. Brick Blue.


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[Assistant] Dr. Blue, Professor of Management at Columbia University.


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[Assistant] has written numbers of articles and books on the topic of making holidays more meaningful in recent years, which is helpful especially to those who are too busy to make perfect private plans. Welcome, Dr. Blue.


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[Assistant] Question 16. Who will benefit particularly from Dr. Brown?


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[Assistant] Which is not mentioned as a way to give kids a sense of continuity and a tradition.


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[Assistant] How could we make kids more enthusiastic to share with others?


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[Assistant] Green is an important color in nature. It is the color of grass and the leaves on trees.


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[Assistant] It is also the color of most growing plants.


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[Assistant] Sometimes the word green means young, fresh, and growing.


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[Assistant] Sometimes it describes something that is not yet ripe or finished.


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[Assistant] For example, a greenhorn is someone who has no experience, who is new to a situation.


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[Assistant] In the 15th century, a greenhorn was a young cow or ox, whose horns had not yet developed.


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[Assistant] A century or so later, a greenhorn was a soldier who had not yet had any experience in battle.


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[Assistant] By the 18th century, a greenhorn had the same meaning it has today. A person who is new in a job.


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[Assistant] Green is also the color used to describe the powerful emotion, jealousy.


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[Assistant] The green-eyed monster is not a frightening creature from outer space. It is an expression used about 400 years ago by British writer William Shakespeare in his play Othello.


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[Assistant] It describes the unpleasant feeling a person has when someone has something he wants.


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[Assistant] A young man may suffer from the green-eyed monster if his girlfriend begins going out with someone else.


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[Assistant] Or, that green-eyed monster may affect your friend if you get a pay raise and she does not.


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[Assistant] In most places in the world, a green light is a sign to move ahead.


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[Assistant] A green light on a traffic signal means your car can continue on.


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[Assistant] In everyday speech, a green light means approval to continue with the project.


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[Assistant] Question 23. According to the speaker.


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[Assistant] How was the review different from early newspapers?


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[Assistant] Question 25. What does the speaker say about the tattler?


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[Assistant] I don't know. I hope not. The meeting's on Friday. But that's not what I want to talk to you about. Uh, close the door, will you?


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[Assistant] I'm worried. I don't know what to do. She's just not performing. We may have to let her go.


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[Assistant] Yes, but lately, the last month or so in fact, there have been a lot of problems. She's changed.


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[Assistant] Not only does she have a tendency to be moody all the time, but she misses appointments, doesn't follow through on projects, and doesn't seem to plan anything till the last minute.


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[Assistant] No. She said she was sorry and that it wouldn't happen again. Something about a mix-up on arrangements to get to the airport.


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[Assistant] Now whenever anybody mentions the subject to her, she just goes silent.


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[Assistant] I don't know. Thank goodness David pulled us out of the hole on that one.


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[Assistant] I don't think it was the first time he's had to do that. If we knew all the facts, I think we'd find that he's been covering for Marsha on quite a few projects.


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[Assistant] Larry arrived early for his speaking engagement.


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[Assistant] He positioned the table so that he could move close to the audience at strategic points in the speech He had read that speakers can be more persuasive


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[Assistant] If they invade the personal space of listeners, encouraging an emotional response.


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[Assistant] For the same reason he placed the chairs close to each other and raised the temperature to a slightly uncomfortable level.


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[Assistant] The purpose of the speech was to encourage the audience of corporate executives and local business owners to support local sports groups.


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[Assistant] To enhance his credibility with the audience, Larry had brought some slides of his family attending sports events.


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[Assistant] One photo showed him at an awards ceremony where he had been honoured for his financial contribution to a local baseball team.


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[Assistant] Realizing that this particular audience would find his regional accent unattractive,


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[Assistant] Larry planned to speak with an accent that would be more acceptable to his audience.


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[Assistant] After reading a book on how to dress for success, he had purchased an expensive dark navy suit and golden tie.


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[Assistant] He chose colors and styles known to communicate power and influence.


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[Assistant] Just before people began entering the hall, Larry dimmed the lights and turned up the sound system, which was playing soft music, hoping to create a warm personal atmosphere for the speech.


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[Assistant] He hoped that these added effects would encourage his audience to support local sports teams.


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[Assistant] He had also planned the content of his speech to focus on the teams with the best records, the ones that had won the most games in the last season.


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[Assistant] What was Wheatley forced to do to get her book published?


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[Assistant] What did Professor Henry Louis Gates uncover in the process of his research?


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[Assistant] I spy with my little eye. You can hear with your little ear.


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[Assistant] A yellow school bus goes beep beep beep.


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[Assistant] And we all go traveling, bye bye bye.


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[Assistant] And we all go traveling by.


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[Assistant] I spy with my little eye You've been here with your little ear Two purple shoes go


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[Assistant] I spy with my little eye.


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[Assistant] It looked great with that green blouse you're wearing. You're weird sir.


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[Assistant] You are to take her to her room, he said. Mr Craven doesn't want to see her. He's going to London in the morning.


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[Assistant] Hmm, that's quite fun actually. Anyway, where was I?


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[Assistant] But all is not well with our Australian friends, and Vet Krista has come to take a closer look. Because Topaz, the kangaroo, has got a problem.


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[Assistant] While Krista considers how best to mend our malfunctioning marsupial, over on Gorilla Island, Silverback Jergen is also starting to feel a bit unwell.


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[Assistant] Back in the kangaroo enclosure, and vet Krista has come up with a plan.


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[Assistant] And it involves a gun? That's a bit extreme, isn't it? Oh, that's not a real gun, is it?


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[Assistant] With the gun loaded and Tobaz safely inside the shed, Krista moves into position.


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[Assistant] In the Vet Center, using a combination of voodoo and medical science, Krista and her team begin the operation. But first, they need to shave her back.


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[Assistant] After some voodoo chanting and some medical scanning, Dr. Krista has finally discovered the cause of the lost harp.


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[Assistant] Now that they know how it happened, it's a race against time to see if the team can finally restore Topaz's lost hob. All Krista can do now is wait. She needs to be patient about her patient. But over on the island, our pretend patient is causing Jeffrey to lose patience.


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[Assistant] It's the moment of truth. Has the Doc's Op unlocked the Stop Top?


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[Assistant] This is a distress code. The coordinates for Washington DC. How is this possible?


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[Assistant] Okay, so the biggest cleaning job is probably cleaning our giraffe beds. I would say it's probably the least favourite as well. And it will take a team of about seven or ten keepers all day to clean out.


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[Assistant] Welcome to Unit 5 of Writing in the Sciences. This week I'm going to walk you through how to write a scientific manuscript.


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[Assistant] Before we jump into the scientific manuscript, however, I do want to briefly continue our discussion from last week on the writing process.


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[Assistant] Is to break the writing up and set very reasonable goals for each day.


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[Assistant] As I'm driving into work, I might tell myself, my goal today is just to write 400 words.


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[Assistant] If I can make 400 words, I will have had a successful day.


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[Assistant] I choose a goal that I know is easy. It's so reasonable and doable that it doesn't seem daunting. It doesn't make me feel like crawling under my desk and curling up in a ball. This makes it easier to get started on the writing that day.


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[Assistant] But it's comforting for me to know in the back of my mind that if for some reason the writing ends up being really tough that day and I can only get to 400 words, I can still call that a success.


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[Assistant] If you set goals too high, like forcing yourself to try to whip out the entire manuscript in one day, this can be so daunting and unrealistic.


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[Assistant] That it makes it hard to even get started. And you'll end up procrastinating and getting nothing done. So set small, doable goals.


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[Assistant] I believe that you need to nail your tables and figures down first.


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[Assistant] Don't just put together some shell tables or something rough.


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[Assistant] But come up with a beautiful, polished set of tables and figures.


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[Assistant] The tables and figures contain the story of your paper.


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[Assistant] Each table and figure should have a clear point, and together they should tell the story of your manuscript.


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[Assistant] So the first thing that you need to do is to figure out that story that your tables and figures are gonna tell.


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[Assistant] And finalize those tables and figures. Make them look professional.


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[Assistant] Once you have a complete set of tables and figures, the results section falls right out of these. So you should write the results next. The results section just gives a high level summary of each table and figure.


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[Assistant] So it's easy to write results if you've done the tables and figures well. Next, I suggest writing the methods.


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[Assistant] You could actually write this at any time because it's just a play by play of what you did, but I think it makes moose sense to write it third. Then you should write the introduction section.


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[Assistant] I think it's important to nail down the story of your manuscript in the tables, figures, and results first before you write the introduction because that helps you to know how to frame the introduction.


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[Assistant] Next you should write the discussion section. That's of course, uh, the hardest to write because it involves the most writing, it's the most complex.


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[Assistant] But having written the rest of the manuscript at this point, it makes it easier to know what to put in the discussion.


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[Assistant] Finally, always do your abstract last. Abstract means to pull out. You are pulling out bits and pieces of the other sections.


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[Assistant] So it's much easier to write after you've already done the other sections.


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[Assistant] If you want to do some further reading, I've given you two references on the page here and I'm going to be citing these two sources throughout the modules this week.


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[Assistant] Uh, first, there's a great series in clinical chemistry. Uh, it goes through, uh, all the parts of the scientific manuscript. And it's, you don't need to be a chemist to benefit from these. Really, these articles apply to any scientific discipline. It's a very well done and easy to read series.


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[Assistant] If you want a longer, more comprehensive reference, I recommend Mimi Zeiger's textbook, The Essentials of Writing Biomedical Research Papers. That's a comprehensive textbook with lots of practice exercises. It's especially useful for those in biomedicine.


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[Assistant] In the first module for this unit, we're going to talk about tables and figures.


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[Assistant] In a lot of ways, the tables and figures are the most important part of the manuscript.


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[Assistant] One big mistake that scientists make is they do the tables and figures kind of haphazardly. They just kind of throw the data into the tables without much thought.


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[Assistant] You need to think through those tables and figures very carefully because they form the foundation of your story.


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[Assistant] Editors, reviewers, and readers may look at the tables and figures first. When I get a paper to review, I skim the abstract just to get a sense of what the paper's about, and then I jump right to the tables and figures.


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[Assistant] I want to look at the data for myself before I read the author's take on their data.


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[Assistant] This means that the tables and figures have to be able to stand alone. They have to be self-contained.


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[Assistant] The reader should not need to refer back to the text to make sense of them.


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[Assistant] Acronyms have to be defined. Experimental details need to be defined.


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[Assistant] Also, each figure and table has to tell a clear story, and they should progress in that story from one to the next.


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[Assistant] Each table and figure should make a clear point and as you're creating the tables and figures you should know what that point is and you should try to stick to that point as much as possible.


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[Assistant] Some people would go so far as to say that the tables and figures are the crooks of the manuscript, and the writing around them is just window dressing.


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[Assistant] I picked out a quote here that's specifically about computational science, but just substitute the word data for the word software here.


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[Assistant] Isn't the scholarship itself, it's merely advertising of the scholarship.


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[Assistant] First of all, you wanna use the fewest figures and tables needed to tell the story.


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[Assistant] Just as in writing prose, you want to be concise and to the point.


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[Assistant] Uh, plus scientific journals may have limits on the numbers of tables and figures that you're allowed to submit.


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[Assistant] Second, don't repeat the same data in both a table and a figure. Choose to present that data as one or the other.


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[Assistant] One of the decisions you're going to have to make is which data belong in a table and which data belong in a figure. What's the difference?


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[Assistant] Figures should have a visual impact. So if you have data that lends itself to a nice, visually appealing graphic, think about putting it in a figure. Figures are used to show trends and patterns.


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[Assistant] Figures also tell a quick story. So if there's a single big point that you want to get across to your readers, that's another thing to put in a figure.


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[Assistant] I like figures because they can give more information about the data. So if you want to show all of your data points rather than just giving summary statistics, for example, or if you want to show the distribution or range of the data, a figure works well for that.


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[Assistant] People also use figures to highlight the most important result of their paper because again


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[Assistant] Figures are visually appealing and they can grab the reader's attention.


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[Assistant] So if there's a specific result you want to emphasize, consider putting that in a figure. Tables are used to give precise values.


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[Assistant] In a figure, you don't usually convey the precise value down to the decimal place. So if you think those precise values are important, you need to put them in a table. And of course, if you have many values with many variables that you need to display, a table is better for displaying a lot of information.


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[Assistant] Every table has a title which should identify the specific topic or point of the table. Remember, every table tells a story and the title should give a quick synopsis of that story.


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[Assistant] Be sure to repeat the same key work, key terms in the table title, the column headings of the table, and in the main text of the paper. Be consistent so that you don't confuse your reader.


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[Assistant] Remember, it's okay to repeat keywords. You want to repeat them so that your reader doesn't get confused.


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[Assistant] You also want to keep the table title concise. Uh, an example title would be descriptive characteristics of the two treatment groups and then means plus or minus standard deviation or n percent.


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[Assistant] This tells the reader the point of the table to describe the two groups and lets them know what statistics to expect.


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[Assistant] Tables also have footnotes, and different journals have different rules for what symbols to use for footnotes.


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[Assistant] Some journals might use stars, whereas others might use letters, A, B, C.


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[Assistant] Don't try to guess. When you are starting to build your tables and figures, identify the journal that you plan to submit the paper to.


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[Assistant] Each journal has its own set of guidelines and the best way to figure out those guidelines is either to read the author's instructions that the journal puts out, or even easier, just pull a paper from that journal and copy the format in their published papers.


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[Assistant] If you're using footnotes to indicate statistically significant differences, make sure to be clear about exactly what comparisons were made, which groups were compared, and what statistical test was used.


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[Assistant] Also use the footnotes to explain experimental details or acronyms. Again, the table has to stand on its own, so any acronyms or definitions or measurement conventions have to be defined within the table. The reader should not have to go back to the text to look those up.


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[Assistant] In formatting tables, there are a ton of little decision points you have to make. Like, do I capitalize the variable names in the table? Do I flush them left or center? Do I use italics? Where do I put the footnotes? What are the footnote symbols?


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[Assistant] Don't guess. Don't try to reinvent the wheel and make all this up from scratch. Just go pull a published paper from the journal you are targeting and copy what you see there.


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[Assistant] Every journal has its own set of style guidelines. You might as well make your tables look like other published papers in the journal you're targeting.


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[Assistant] Reviewers and editors are impressed when they see professional looking tables in that journal's style.


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[Assistant] Another thing to keep in mind is that the convention for most journals is that tables contain just three horizontal lines. One above the column headings, one below the column headings, and one below the data. A lot of people are unaware of this, so they put in many more lines than this, and it ends up looking unprofessional.


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[Assistant] Here's an example table with some made-up data. When my daughter was two, uh, The Wizard of Oz was her favorite movie.


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[Assistant] And uh, there's a line in that movie where the Good Witch asks Dorothy,


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[Assistant] Are you a bad witch or a good witch? So they have bad witches and good witches in Oz.


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[Assistant] So I made up some pretend data on bad witches and good witches. In my hypothetical study, I have 13 bad witches and 12 good witches.


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[Assistant] I've measured their descriptive characteristics and put it into a descriptive table, which is your typical table one for a medical study.


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[Assistant] This is what a typical table looks like. Notice the three horizontal lines. One, uhm, above the column headings, one below the column headings, and one below the data before the footnotes. That's how most journals format their tables.


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[Assistant] Notice that this table has a simple clear point to compare the two groups of witches.


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[Assistant] And we can quickly glean what's different about the two groups. Bad witches are older, less healthy, and somewhat less employed.


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[Assistant] Some journals, uh, will also gray out every other row to help readers distinguish one row from the next. Notice there are still just those three horizontal lines, but the shading helps guide the reader's eyes. This also looks very professional.


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[Assistant] Now I'm going to show you some things that you should avoid doing in your tables. Okay, first of all, I mentioned earlier the importance of getting grid lines correct. You should have just those three horizontal lines.


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[Assistant] Here's a table in which they have included all of the grid lines.


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[Assistant] And it might seem like a minor point, but the problem is that the table looks unprofessional. This is not how tables appear in journals.


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[Assistant] I make a big point of this with my students at Stanford because I've reviewed many, many papers over the years. And at some point I noticed that papers with tables like this, with all the grid lines, tend to have lots of problems elsewhere in the paper.


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[Assistant] Maybe using all the grid lines like this is more common among new authors who don't have much paper writing experience. Or maybe it's just a mark of general sloppiness. But I noticed this correlation between the presence of the grid lines and problems elsewhere in the paper.


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[Assistant] So when I flip the tables to the tables and I see all those grid lines, there's a red flag that goes off in my head.


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[Assistant] I automatically expect that the paper is going to have other problems.


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[Assistant] I suspect that other reviewers and editors have formed the same association in their heads, either consciously or unconsciously.


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[Assistant] And I've actually had several students come back to me after taking my course and say that they started noticing this association between the presence of all the grid lines and poor quality papers.


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[Assistant] So you don't want to make this mistake because it's a red flag for reviewers and editors. It might seem like a trivial thing, but it signals to reviewers and editors that your paper is sloppy and unprofessional. Always take the time to get those grid lines right.


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[Assistant] Figure out in your word processing program how to get rid of the extra grid lines. Make your tables look professional.


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[Assistant] Another thing that doesn't look professional is if your columns and data are misaligned. You can see here that items in the columns are not lined up nicely.


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[Assistant] They don't usually look as bad as this. I've exaggerated for effect here, but you'll often see numbers that aren't perfectly lined up, especially when decimal places are involved.


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[Assistant] I also have some words here beginning with capitals and others beginning with lowercase. I mixed it up.


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[Assistant] This inconsistency also looks unprofessional.


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[Assistant] This kind of sloppiness makes a big negative impression on reviewers and editors, so take the time to make your tables look professional.


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[Assistant] Another problem I see with a lot of tables is people love to go out to a ridiculous number of significant figures.


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[Assistant] I think that's because if you put something like age into your statistical analysis program,


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[Assistant] Your computer will spit out values like the average age or the average BMI to several decimal places.


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[Assistant] And then people just cut and paste the value into their tables without thinking about it.


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[Assistant] But we don't need to know BMI to the third decimal place, and it just clutters the table.


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[Assistant] You should only go out to as many decimal places as you can claim as significant figures. So if you only measured BMI to one decimal place, your summary statistics for BMI should not have more than one decimal place.


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[Assistant] Also, always give units for the variables in your table. A lot of my students forget to include units when listing variables like this.


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[Assistant] I think it's easy to forget the units when again you're just cutting and pasting output from your statistical analysis program. But the units are often ambiguous.


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[Assistant] For example, what does exercise mean here? Is that 30 minutes a day? Is that 30 minutes a week? Is that 60 minutes a year? Is that 60 hours a year? There's no way to tell without having the units.


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[Assistant] Even age may seem obvious. You may assume that 45 and 36 is referring to years here. But we don't know for sure. It could be months if we are talking about toddlers. So units are essential.


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[Assistant] Another mistake people make on tables is to include too many columns. I had a nice, crisp table to begin with. It was easy to see that the goal of the table was to compare bad witches and good witches.


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[Assistant] It was easy to glean that bad witches seemed to be older and less healthy than good witches.


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[Assistant] Adding extra columns just attracts from this nice simple message.


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[Assistant] Here we have an overall column. That overall column is extra information that doesn't have to do with the comparison.


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[Assistant] And if a reader really wanted to know the overall value for some reason, they could calculate it from the other data in the table. So it just adds clutter.


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[Assistant] Similarly, statistical significance can be neatly indicated using subscripts and footnotes as I did in the original table.


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[Assistant] The point of the p-values here is just to flag statistically significant differences, which can be done with a star and a footnote.


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[Assistant] There may be instances when it's important to show the exact p-values for all the different variables, but I don't think that's the case here. Here readers just need to be able to quickly glean which variables differ significantly. Extra columns make the table hard to read,


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[Assistant] Alright, now moving on to figures. There are three types of figures that we're going to talk about.


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[Assistant] They're in there to show the quality of the data.


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[Assistant] And also because there's a seeing is believing element to these. If readers can see the lines on the gel for themselves, they're more confident in the results.


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[Assistant] Primary evidence is usually pretty straightforward to create because it's just pictures or movies. Second, there's graphs.


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[Assistant] These are graphical ways of displaying your data. Things like line graphs, bar graphs, and scatter plots. I'll talk more about these in a minute.


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[Assistant] Finally, there are drawings and diagrams.


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[Assistant] They have really nice uses. You can do, use them to do things like illustrate an experimental setup or a workflow.


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[Assistant] Or to indicate the flow of participants in your study.


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[Assistant] Or to illustrate cause and effect relationships or cycles.


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[Assistant] Drawings and diagrams can convey key information to the reader that might be quite tedious and convoluted when written in prose.


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[Assistant] Uhm, and sometimes it's nice, you can give a hypothetical model, or it's nice to represent things that you can't see, like microscopic particles or microorganisms. Sometimes it's helpful to represent those as cartoons, that can be nice for the reader to have a visual of something that they couldn't otherwise see.


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[Assistant] Uhm, so I'm going to go through each of these types of figures now in turn.


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[Assistant] Of course, all your figures will have a legend. You need the legend so that the figure can stand alone.


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[Assistant] It should have a brief, informative title that conveys the main point of the figure.


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[Assistant] It should contain essential experimental details so that the reader doesn't have to go back and read the main text.


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[Assistant] You'll also have a legend to define symbols, lines, or patterns, or to explain what's in different panels, if you have like an A, B, C, D, and E panel.


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[Assistant] Or if you want to get, you're going to need to also to give statistical details such as what tests were used and what the p-values, where did those p-values come from, what the p-values were.


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[Assistant] Here's an example of a figure legend. This is from a study that found that tomato and Arabidopsis plants, uh, kind of eat microbes, such as E. coli bacteria. I'm not going to read through the legend, but you can see that it has an informative title and sufficient experimental details that the figure can stand on its own.


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[Assistant] This is the figure that goes with the legend I just showed you. You'll notice there's a lot of different panels in this figure.


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[Assistant] They also have some letters and arrows in the panels. You'll notice all the little white arrows and there are some letters like E, M, and R. All of this has to be explained in the legend.


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[Assistant] This was a paper where they were showing that plants actually eat microbes like E. coli. So that's a cool paper with some very cool images.


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[Assistant] Those green parts are the E. coli being taken up by the plant roots. The plants are actually eating the microbes. So this is primary evidence. It's showing you, hey, here it is. Here's the E. coli in the plant roots. Seeing is believing. Here's another example of primary evidence, a gel.


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[Assistant] Next I'm going to jump to graphs. Uh, I could teach a whole course on graphs. You really need a whole course on data visualization to do justice to this topic.


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[Assistant] And it's such an important topic that I'd actually recommend that you do take a course in data visualization in the future.


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[Assistant] Among the most common types of graphs are line graphs, scatter plots, bar graphs, individual value bar graphs, histograms, box plots, and survival curves.


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[Assistant] I'm going to go through each of these, so line graphs show trends over time.


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[Assistant] Or something trends over something that's increasing or decreasing, like age or dose. Typically,


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[Assistant] Just to give you an example, here's a line graph that compares two groups. A treatment group, which is in green, and a control group, which is in red.


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[Assistant] They are tracking what happens to the number of positive cells.


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[Assistant] This graph tells a quick story. Increasing DPI that your X variable access, your X axis variable doesn't seem to affect the control group much. The red line's pretty flat.


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[Assistant] So it tells a quick visual story. The one thing that's a bit confusing in this graph is I don't like the stars on top. These probably have to do with statistical significance, but it's not immediately obvious what they mean.


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[Assistant] Okay, bar graphs. Bar graphs are used to compare groups at one time point, or one dose.


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[Assistant] Everybody loves bar graphs because they are easy to understand, they tell a quick visual story, and your reader doesn't have to do too much work to understand a bar graph. So here are some examples.


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[Assistant] This was from that study looking at tomato plants eating E. coli. They have two controls and a treatment.


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[Assistant] And the treatment group clearly takes up more E. coli. They incorporate more of the microbes.


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[Assistant] That's easy to glean from the graph. There are a few things I'm gonna point out on this, uh, graph that I would improve. Uh, for example, it's not immediately clear to me what the A, B, and C mean. If possible, it's best to not make the reader have to go to the legend to figure that out, make it something more obvious.


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[Assistant] It's not, also not terribly, uhm, beautiful visually because they've left the bars with white spaces. Uhm, usually shading those bars makes it look a little bit nicer.


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[Assistant] So here's another example. This one's a little bit more visually appealing. Notice they've shaded the bars in gray.


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[Assistant] Uh, this graph also appears to be at higher resolution. It's sharper and crisper than the graph I just showed you.


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[Assistant] Normally people leave this information off, but it's so important for the reader to have that information at their fingertips that I love to see it put on the graph like this.


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[Assistant] So this is a nice bar graph that has a clear take on point. The outcome.


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[Assistant] Uh, average degree is increasing over increasing concentrations.


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[Assistant] Next, scatter plots. Scatter plots are used to show relationships between two variables, uh, usually to continuous or to numeric variables.


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[Assistant] I love scatter plots because they show all the data.


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[Assistant] Most graphs and tables just show summary statistics, but you don't get to see all the individual data points.


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[Assistant] The scatter plot is great because it shows everything about the data. It shows all the individual data points, so it gives you more information.


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[Assistant] It really gives the reader a sense of what's going on in the data instead of just giving one perspective on the data. In a way, it shows all the dirty laundry.


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[Assistant] So I like Scatterplus because you can see those individual data points. Let me give you some examples.


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[Assistant] This scatterplot is from a study that was looking at high grade and low grade brain tumors. The high grade tumors are in red.


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[Assistant] The low-grade tumors are in blue. And the graph shows the correlation between expression levels of a particular gene that's on the x-axis and levels of the biomarker CD44 that's on the y-axis.


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[Assistant] You can see that you're getting a lot more information from a plot like this.


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[Assistant] The high-grade tumors in red have a higher level of both the gene expression and the CD44 biomarker than the low-grade tumors. You can see the red is more in the upper right-hand corner than the blue is.


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[Assistant] But what you can see here that you wouldn't be able to glean from summary statistics is that there's a lot of variation in that red group. Some of the


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[Assistant] People in the red, or the tumors in the red group have very high levels of both, but we also have, uh, tumors that have low levels of both. So there's high variation here.


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[Assistant] You'll also notice that the relationship between the gene expression and the biomarker, it's not a straight line relationship, it's a bit curved.


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[Assistant] So you can see that this shape here is not exactly a total linear relationship.


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[Assistant] So I love scatter plots because they give you so much information. Again, you're kind of airing your dirty laundry, but that allows the reader to get a really good feel for what's going on in your data.


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[Assistant] One caution on scatter plots though, if you are going to superimpose either straight lines or curved lines like they have here, just be aware that these lines can fool the eye.


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[Assistant] In the plot I'm showing here, there is a clear straight line relationship between x and y. So it's perfectly appropriate to superimpose a straight line, a regression line on that plot.


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[Assistant] But be careful because sometimes lines can fool the eye. So I'm going to show you that now.


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[Assistant] So here's a scatter plot that I made. I just made up some data. An x variable and a y variable. And then


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[Assistant] I superimposed a line on that. If you just glance at this quickly, it looks like there's a nice inverse relationship between x and y, right? It's actually an illusion though.


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[Assistant] It makes you see an inverse relationship between x and y. It makes it appear that those two have an inverse relationship.


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[Assistant] And just to show you that this is really just a visual trick, I also superimposed a 90 degree line in the positive direction. And notice that this is the exact same scatter plot, but when I put the uhm, the line in the other direction, all of a sudden, your eye starts to think that there is a positive correlation between x and y.


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[Assistant] But of course, both of these are just your eye being fooled because if I take the lines off of this graph, you can see that there is actually no relationship whatsoever between x and y. So it's easy to, uhm, to fool your eye.


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[Assistant] Be careful when you're superimposing lines because it can make relationships look stronger than they really are and this can be misleading. A few tips for graphs.


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[Assistant] Again, graphs are supposed to tell a quick visual story. So you want to keep it simple. You want to make it easy on your reader. Instead of representing different groups with arbitrary symbols such as


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[Assistant] Filled in circles or unfilled circles or squares or triangles try to be a bit more clever than this.


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[Assistant] This is much easier on the reader because they don't have to keep referring back to the legend.


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[Assistant] Also, use different colors for different groups.


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[Assistant] When I learned to make graphics, uh, we used to have to use dashed lines, uh, and solid lines to distinguish groups because you had to assume that your paper was going to be red in black and white. People would copy papers out of journals and the copies would always be black and white.


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[Assistant] Well, now we're in an era when you can use color. Most everyone is reading papers on an electronic device, so you can go ahead and use colors to distinguish different groups. That's much easier on the reader.


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[Assistant] The line graphs on the left side of the slide are quite nice. I like those line graphs. You can see that there are four groups and the proportion of cooperation, that's your y variable, is going down over time in all the groups except one.


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[Assistant] That group in red seems to be different than the other three groups in terms of the trajectory. So that line graph tells a nice story.


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[Assistant] But then the authors also added a bar graph to the figure on the right hand side. And this is summarizing the same data that are in the line graph.


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[Assistant] What they did is they averaged sessions five through ten so that they could show that the red group was on average in those five sessions statistically higher than the other three groups. The stars are supposed to be indicating statistically significant differences here.


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[Assistant] But it's very confusing. Those stars, it's not clear what comparisons they're referring to.


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[Assistant] Uh, plus seeing the data points from the individual sessions is much more informative than just seeing an average of an arbitrary number of sessions. So I don't think you gain anything by adding the bar graph to this figure. It just serves to clutter the graph and confuse the reader.


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[Assistant] The authors could have just added a star somewhere on the line graph to indicate that the red group differed from the other three based on a statistical test that compares the trajectories over time.


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[Assistant] Uhm, one other tip here, notice that the line graph uses squares, triangles, diamonds, and circles to differentiate the different groups.


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[Assistant] It's a little hard on the reader because the reader has to keep looking back to the legend to figure out which group is which. Maybe the authors could have labeled the groups, uh, the group names on the graph somewhere or used more informative plotting symbols.


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[Assistant] Here's another example where the graph has too much going on. It's not telling a clear and simple story. The bar graphs are too cluttered, there's too much data, there are no clear patterns, so it's not obvious what the take home point is supposed to be.


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[Assistant] If the data are this complicated, you may be better off presenting them in a table rather than a figure. A figure is supposed to tell a simple visual story, and I don't think this one accomplishes that.


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[Assistant] You have diagrams and drawings at your disposal and these are underused, I think, in the scientific literature. They can be very powerful.


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[Assistant] For example, many things don't lend themselves well to text, such as explaining the flow of participants in a study, or the details of an experimental setup. Often a picture is better for conveying this information.


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[Assistant] Also, if you have some kind of hypothetical cause and effect model that you're trying to propose, a diagram is great for indicating how you think those variables interact, especially if the relationships are complex.


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[Assistant] This may all be better put in a picture than trying to explain it in some complicated text.


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[Assistant] Also if you're talking about something people can't see like viruses or proteins or antibodies, a cartoon can help your reader visualize what you're talking about. So think about in your paper if there's places where you could use a diagram or drawing to your advantage. I'll give you some examples.


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[Assistant] Here's a figure from a paper that was looking at drug company advertisements in journals.


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[Assistant] Bottom right hand corner, you always have your Kaplan-Meier survival curve.


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[Assistant] A picture is worth a thousand words here. If you tried to describe this setup in prose, it would be uninteresting to read. It would be boring to read, and it would be much harder to convey that information. This is visual information, so might as well put it in a drawing.


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[Assistant] I love this diagram. This was in a paper describing dog bites and cat bites in human patients. Rather than just sticking the data into a boring table, the authors were clever enough to put it in a picture.


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[Assistant] Nice way to present the data than just putting it in a boring table.


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[Assistant] Diagrams are great for drawing causal diagrams like this. You can see how this is much simpler to present in a diagram than to try to explain all those relationships and prose.


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[Assistant] And finally, here's a cartoon illustration of the creation of some novel antibodies. Again, the picture is really helpful to the reader in understanding how these antibodies are built.


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[Assistant] And the final thing I want to mention is that nowadays, you're not just limited to tables and figures. Your papers can have videos.


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[Assistant] This is back to the paper on plants eating microbes for nutrients.


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[Assistant] Seeing is believing applies even more for movies than for still pictures. So we can play this little video and actually see the, uh, microbes being taken up by the plant.


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[Assistant] I actually came to get some water out one day and there was one swimming along the edge of the bank.


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[Assistant] Uh, sort of a greeny grey. I have filmed them once, I filmed them when I was over feeding the flamingos.


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[Assistant] Mary knew she had to answer Colin's questions about the secret garden, but she didn't want to.


[User] Please transcribe this text

[Assistant] But it was too late to be careful. Colin was just like Mary. He'd had nothing to think about for years.


[User] Please transcribe this text

[Assistant] So the idea of a hidden garden interested him, just as it had interested her.


[User] Please transcribe this text

[Assistant] He asked question after question. Where was it?


[User] Please transcribe this text

[Assistant] Had she looked for the door? Had she asked the gardeners?


[User] Please transcribe this text

[Assistant] If Colin could force people to answer, who knew what might happen?