1.5: Fitting Linear Models to Data
Learning Objectives
- Draw and interpret scatter plots.
- Use a graphing utility to find the line of best fit.
- Fit a regression line to a set of data and use the linear model to make predictions.
Prerequisite Skills
Before you get started, take this prerequisite quiz.
1. On a piece of graph paper, plot and label these points: A(1, 4), B(-3, 2), C(2, -5), D(0, -3), E(4, 0).
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-
If you missed any part of this problem, review here . (Note that this will open a different textbook in a new window.)
2. Write the coordinates of each of the points shown in this graph.
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A(0, 5)
B(2, 4)
C(-3, -1)
D(-4, 0)
E(3, -4)
If you missed any part of this problem, review here . (Note that this will open a different textbook in a new window.)
3. If \(y=-3.215x-78.2\), solve for \(y\) when \(x=-21\).
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\(y=-10.685\)
If you missed this problem, review here . (Note that this will open a different textbook in a new window.)
4. If \(y=-3.215x-78.2\), solve for \(x\) when \(y=-46.05\).
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\(x=-10\)
If you missed this problem, review Section 1.1 . (Note that this will open in a new window.)
A professor is attempting to identify trends among final exam scores. His class has a mixture of students, so he wonders if there is any relationship between age and final exam scores. One way for him to analyze the scores is by creating a diagram that relates the age of each student to the exam score received. In this section, we will examine one such diagram known as a scatter plot.
Drawing and Interpreting Scatter Plots
A scatter plot is a graph of plotted points that may show a relationship between two sets of data. If the relationship is from a linear model , or a model that is nearly linear, the professor can draw conclusions using his knowledge of linear functions. Figure \(\PageIndex{1}\) shows a sample scatter plot.
Notice this scatter plot does not indicate a linear relationship . The points do not appear to follow a trend. In other words, there does not appear to be a relationship between the age of the student and the score on the final exam.
To create a scatter plot on a calculator
- Press STAT ENTER to enter your data; enter your \(X\) data into list L1 and your \(Y\) data into list L2.
- Press 2nd STATPLOT ENTER to use Plot 1. On the input screen for PLOT 1, highlight On and press ENTER. (Make sure the other plots are OFF.)
- For TYPE: highlight the very first icon, which is the scatter plot, and press ENTER.
- For Xlist:, enter L1 ENTER and for Ylist: L2 ENTER.
- For Mark: it does not matter which symbol you highlight, but the square is often the easiest to see. Press ENTER.
- Make sure there are no other equations that could be plotted. Press Y = and clear any equations out.
- Press the ZOOM key and then the number 9 (for menu item "ZoomStat"); the calculator will fit the window to the data. You can press WINDOW to see the scaling of the axes.
Example \(\PageIndex{1}\): Using a Scatter Plot to Investigate Cricket Chirps
The table below shows the number of cricket chirps in 15 seconds, for several different air temperatures, in degrees Fahrenheit. Plot this data in your calculator, and determine whether the data appears to be linearly related.
| Chirps | 44 | 35 | 20.4 | 33 | 31 | 35 | 18.5 | 37 | 26 |
| Temperature | 80.5 | 70.5 | 57 | 66 | 68 | 72 | 52 | 73.5 | 53 |
Solution
Plotting this data, as depicted in Figure \(\PageIndex{2}\) suggests that there may be a trend. We can see from the trend in the data that the number of chirps increases as the temperature increases. The trend appears to be roughly linear, though certainly not perfectly so.
Finding the Line of Best Fit
Once we recognize a need for a linear function to model that data, the natural follow-up question is “what is that linear function?” One way to approximate our linear function is to sketch the line that seems to best fit the data. Then we can extend the line until we can verify the y-intercept. We can approximate the slope of the line by extending it until we can estimate the \(\frac{\text{rise}}{\text{run}}\).
Example \(\PageIndex{2}\): "Eyeballing" a Line of Best Fit
Find a linear function that fits the data in Table \(\PageIndex{1}\) by “eyeballing” a line that seems to fit.
Solution
On a graph, we could try sketching a line.
Using the starting and ending points of our hand drawn line, points \((0, 30)\) and \((50, 90)\), this graph has a slope of
\[m=\dfrac{60}{50}=1.2\nonumber\]
and a y-intercept at 30. This gives an equation of
\[T(c)=1.2c+30\nonumber\]
where \(c\) is the number of chirps in 15 seconds, and \(T(c)\) is the temperature in degrees Fahrenheit. The resulting equation is represented in Figure \(\PageIndex{3}\).
Analysis
This linear equation can then be used to approximate answers to various questions we might ask about the trend.
Exercise \(\PageIndex{1}\)
According to the data from Table \(\PageIndex{1}\), what temperature can we predict it is if we counted 20 chirps in 15 seconds?
Solution
54°F
Finding the Line of Best Fit Using a Graphing Utility
While eyeballing a line works reasonably well, some statistical techniques exist for fitting a line to data that minimize the differences between the line and data values[2]. One such technique is called least squares regression and can be computed by many graphing calculators, spreadsheet software, statistical software, and many web-based calculators[3]. Least squares regression is one means to determine the line that best fits the data, and here we will refer to this method as linear regression.
Given data of input and corresponding outputs from a linear function, find the best fit line using linear regression.
Example \(\PageIndex{3}\): Finding a Linear Regression Equation
Find the line of best fit using the cricket-chirp data in Table \(\PageIndex{1}\).
Solution
Enter the input (chirps) in List 1 (L1).
Enter the output (temperature) in List 2 (L2). See Table \(\PageIndex{2}\).
| L1 | 44 | 35 | 20.4 | 33 | 31 | 35 | 18.5 | 37 | 26 |
| L2 | 80.5 | 70.5 | 57 | 66 | 68 | 72 | 52 | 73.5 | 53 |
To use a calculator to find the equation of this line:
- In the STAT list editor, enter the \(X\) data in list L1 and the Y data in list L2, paired so that the corresponding (\(x,y\)) values are next to each other in the lists. (If a particular pair of values is repeated, enter it as many times as it appears in the data.)
- On the STAT TESTS menu, scroll down with the cursor to select the LinRegTTest. (Be careful to select LinRegTTest, as some calculators may also have a different item called LinRegTInt.)
- On the LinRegTTest input screen enter: Xlist: L1 ; Ylist: L2 ; Freq: 1
- On the next line, at the prompt \(\beta\) or \(\rho\), highlight "\(\neq 0\)" and press ENTER
- Leave the line for "RegEq:" blank
- Highlight Calculate and press ENTER.
The output screen contains a lot of information. For now we will focus on a few items from the output, and will return later to the other items.
The second line says \(y = a + bx\). Scroll down to find the values for a and b for the equation of the line of best fit.
Therefore we obtain the equation:
\[y=30.281+1.143x \nonumber \]
or
\[T=30.281+1.143c \nonumber \]
Analysis
To graph the best-fit line, press the "\(Y =\)" key and type the equation \(30.281 + 1.143X\) into equation Y1. (The \(X\) key is immediately left of the STAT key). Press ZOOM 9 again to graph it.
Notice that this line is quite similar to the equation we “eyeballed” but should fit the data better. Notice also that using this equation would change our prediction for the temperature when hearing 30 chirps in 15 seconds from 66 degrees to:
\[\begin{align*} T(30)&=30.281+1.143(30) \\ &=64.571 \\ &\approx 64.6 \text{ degrees} \end{align*} \]
The graph of the scatter plot with the line of best fit is shown in Figure \(\PageIndex{4}\).
Will there ever be a case where two different lines will serve as the best fit for the data?
No. There is only one best fit line.
Predicting with a Regression Line
Once we determine that a set of data is linear, we can use the regression line to make predictions. As we learned above, a regression line is a line that is closest to the data in the scatter plot, which means that only one such line is a best fit for the data.
Example \(\PageIndex{4}\): Using a Regression Line to Make Predictions
Gasoline consumption in the United States has been steadily increasing. Consumption data from 1994 to 2004 is shown in Table \(\PageIndex{3}\). Graph the data and determine whether the trend is linear. If so, find a model for the data and use the model to predict the consumption in 2008.
| Year | '94 | '95 | '96 | '97 | '98 | '99 | '00 | '01 | '02 | '03 | '04 |
| Consumption (billions of gallons) | 113 | 116 | 118 | 119 | 123 | 125 | 126 | 128 | 131 | 133 | 136 |
The scatter plot of the data, including the least squares regression line, is shown in Figure \(\PageIndex{5}\).
We can introduce new input variable, \(t\),representing years since 1994.
The linear regression equation is:
\[C(t)=113.318+2.209t \nonumber \]
Using this to predict consumption in 2008 \((t=14)\),
\[\begin{align*} C(14)&=113.318+2.209(14) \\ &=144.244 \end{align*} \]
The model predicts 144.244 billion gallons of gasoline consumption in 2008.
Exercise \(\PageIndex{2}\)
Use the model we created using technology in Example \(\PageIndex{4}\) to predict the gas consumption in 2011.
- Answer
-
150.871 billion gallons
Key Concepts
- Scatter plots show the relationship between two sets of data.
- Scatter plots may represent linear or non-linear models.
- The line of best fit may be estimated or calculated, using a calculator or statistical software.
- The correlation coefficient, \(r\), indicates the degree of linear relationship between data.
- A regression line best fits the data.
- The least squares regression line is found by minimizing the squares of the distances of points from a line passing through the data and may be used to make predictions regarding either of the variables.
Contributors and Attributions
-
Jay Abramson (Arizona State University) with contributing authors. Textbook content produced by OpenStax College is licensed under a Creative Commons Attribution License 4.0 license. Download for free at https://openstax.org/details/books/precalculus .


4.4: Designing a Database
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- Last updated
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- Ly-Huong T. Pham, Tejal Desai-Naik, Laurie Hammond, & Wael Abdeljabbar
- ASCCC Open Educational Resources Initiative (OERI)
Designing a Database
Suppose a university wants to create a database to track participation in student clubs. After interviewing several people, the design team learns that implementing the system is to give better insight into how the university funds clubs. This will be accomplished by tracking how many members each club has and how active the clubs are. The team decides that the system must keep track of the clubs, their members, and their events. Using this information, the design team determines that the following tables need to be created:
- Clubs: this will track the club name, the club president, and a short description of the club.
- Students: student name, e-mail, and year of birth.
- Memberships: this table will correlate students with clubs, allowing us to have any given student join multiple clubs.
- Events: this table will track when the clubs meet and how many students showed up.
Now that the design team has determined which tables to create, they need to define the specific information that each table will hold. This requires identifying the fields that will be in each table. For example, Club Name would be one of the fields in the Clubs table. First Name and Last Name would be fields in the Students table. Finally, since this will be a relational database, every table should have a field in common with at least one other table (in other words: they should have a relationship with each other).
To properly create this relationship, a primary key must be selected for each table. This key is a unique identifier for each record in the table. For example, in the Students table, it might be possible to use students’ first names to identify them uniquely. However, it is more than likely that some students will share the last name (like Mike, Stefanie, or Chris), so a different field should be selected. A student’s email address might be a good choice for a primary key since e-mail addresses are unique. However, a primary key cannot change, so this would mean that if students changed their email addresses, we would have to remove them from the database and then re-insert them – not an attractive proposition. Our solution is to create a value for each student — a user ID — that will act as a primary key. We will also do this for each of the student clubs. This solution is quite common and is the reason you have so many user IDs!
You can see the final database design in the figure below:
With this design, not only do we have a way to organize all of the information we need to meet the requirements, but we have also successfully related all the tables together. Here’s what the database tables might look like with some sample data. Note that the Memberships table has the sole purpose of allowing us to relate multiple students to multiple clubs.
Normalization
When designing a database, one important concept to understand is normalization. In simple terms, to normalize a database means to design it in a way that:
- Reduces redundancy of data between tables easier mapping
- Takes out inconsistent data.
- Information is stored in one place only.
- Gives the table as much flexibility as possible.
In the Student Clubs database design, the design team worked to achieve these objectives. For example, to track memberships, a simple solution might have been to create a Members field in the Clubs table and then list all of the members' names. However, this design would mean that if a student joined two clubs, then his or her information would have to be entered a second time. Instead, the designers solved this problem by using two tables: Students and Memberships.
In this design, when a student joins their first club, we must add the student to the Students table, where their first name, last name, e-mail address, and birth year are entered. This addition to the Students table will generate a student ID. Now we will add a new entry to denote that the student is a specific club member. This is accomplished by adding a record with the student ID and the club ID in the Memberships table. If this student joins a second club, we do not have to duplicate the student’s name, e-mail, and birth year; instead, we only need to make another entry in the Memberships table of the second club’s ID and the student’s ID.
The Student Clubs database design also makes it simple to change the design without major modifications to the existing structure. For example, if the design team was asked to add functionality to the system to track faculty advisors to the clubs, we could easily accomplish this by adding a Faculty Advisors table (similar to the Students table) and then adding a new field to the Clubs table to hold the Faculty Advisor ID.
Data Types
When defining the fields in a database table, we must give each field a data type. For example, the field Birth Year is a year, so it will be a number, while First Name will be text. Most modern databases allow for several different data types to be stored. Some of the more common data types are listed here:
- Text: for storing non-numeric data that is brief, generally under 256 characters. The database designer can identify the maximum length of the text.
- Number: for storing numbers. There are usually a few different number types selected, depending on how large the largest number will be.
- Yes/No: a special form of the number data type that is (usually) one byte long, with a 0 for “No” or “False” and a 1 for “Yes” or “True.”
- Date/Time: a special form of the number data type can be interpreted as a number or a time.
- Currency: a special form of the number data type that formats all values with a currency indicator and two decimal places.
- Paragraph Text: this data type allows for text longer than 256 characters.
- Object: this data type allows for data storage that cannot be entered via keyboards, such as an image or a music file.
The importance of properly defining data type is to improve the data's integrity and the proper storing location. We must properly define the data type of a field, and a data type tells the database what functions can be performed with the data. For example, if we wish to perform mathematical functions with one of the fields, we must tell the database that the field is a number data type. So if we have a field storing birth year, we can subtract the number stored in that field from the current year to get age.
Allocation of storage space for the defined data must also be identified. For example, if the First Name field is defined as a text(50) data type, fifty characters are allocated for each first name we want to store. However, even if the first name is only five characters long, fifty characters (bytes) will be allocated. While this may not seem like a big deal, if our table ends up holding 50,000 names, we allocate 50 * 50,000 = 2,500,000 bytes for storage of these values. It may be prudent to reduce the field's size, so we do not waste storage space.


4.1: Prelude to Motion in Two and Three Dimensions
To give a complete description of kinematics, we must explore motion in two and three dimensions. After all, most objects in our universe do not move in straight lines; rather, they follow curved paths. From kicked footballs to the flight paths of birds to the orbital motions of celestial bodies and down to the flow of blood plasma in your veins, most motion follows curved trajectories.
Fortunately, the treatment of motion in one dimension in the previous chapter has given us a foundation on which to build, as the concepts of position, displacement, velocity, and acceleration defined in one dimension can be expanded to two and three dimensions. Consider the Red Arrows, also known as the Royal Air Force Aerobatic team of the United Kingdom. Each jet follows a unique curved trajectory in three-dimensional airspace, as well as has a unique velocity and acceleration. Thus, to describe the motion of any of the jets accurately, we must assign to each jet a unique position vector in three dimensions as well as a unique velocity and acceleration vector. We can apply the same basic equations for displacement, velocity, and acceleration we derived in Motion Along a Straight Line to describe the motion of the jets in two and three dimensions, but with some modifications—in particular, the inclusion of vectors.
In this chapter we also explore two special types of motion in two dimensions: projectile motion and circular motion. Last, we conclude with a discussion of relative motion. In the chapter-opening picture, each jet has a relative motion with respect to any other jet in the group or to the people observing the air show on the ground.


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anorexia nervosa
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a culture-bound syndrome present in North American and European cultures, characterized by a person not eating to meet beauty standards.
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authoritative knowledge
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authority derived from perceived legitimacy, dependent on culture.
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biocultural approach
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the assumption that culture is informed by physical and sociocultural elements.
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biomedicine
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health care systems rooted in European and North American scientific knowledge.
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Blue Zones
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communities around the world with a high concentration of people near or over the age of 100.
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causal attributions
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a psychological concept used to study regular cultural behavior and how deviation from that behavior might be explained.
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clinical observations
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an ethnographic method resulting in a straightforward, clinical study of a medical situation.
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comorbidities
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two or more health conditions that often occur together.
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critical medical anthropology (CMA)
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a theory that highlights a culture’s inequalities, including inequalities in health care.
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critical theories of health
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an applied theory aimed at pointing out issues within health care systems and changing them for the better.
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cultural concepts of distress (CCD)
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a psychological term used to describe the way a culture experiences and expresses distress.
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cultural systems model
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a theory that that analyzes how systems within a particular culture, including health care systems, affect one’s worldview and actions.
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disease
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a biological agent that negatively affects health.
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epigenetics
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the changes in gene expression that take place during a person’s lifetime, often through environmental exposure.
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ethnomedicine
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a culture’s traditional knowledge and treatments for the management of health and illness.
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evolutionary medicine
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a method that uses evolutionary biology and culture to better understand human health.
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health
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health decision-making analysis
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idioms of distress
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illness
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a person’s experience of ill health, as defined by their culture.
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an ethnographic method used to collect information about an informant’s illness experience in their own words.
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malady
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a term encompassing disease, illness, and sickness.
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a multidisciplinary theory studying the effects of environment on lifestyle and health.
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a methodology in which the anthropologist makes first-person observations while participating in a culture.
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placebo effect
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the effect in which belief in a treatment’s efficacy creates a positive health outcome.
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a theory that highlights a culture’s inequalities, including inequality in health care.
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political economy
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the connection of economics and politics and how they affect wealth and inequality.
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a cultural response to stress and trauma in Latinx communities.
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the social intersection of comorbidities in health outcomes.
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13: Sexual Health Last updated Save as PDF Page ID 167232 Susan Rahman with Nathan Bowman, Dahmitra Jackson, Lushtak, Remi Newman, & Prateek Sunder California Consortium for Equitable Change in Hispanic Serving Institutions Open Educational Resources (CC ECHO) 13.1: Introduction to Sexual Health 13.2: Some Definitions on Sexual Health 13.3: Our Sexuality Includes 13.4: Sexual Health- Why does it matter? 13.5: The Prostate 13.6: We Asked! Answers to Some Questions from Jamie Weinstein, MD, Family Physician 13.7: What About Libido? 13.8: For Folks into BDSM and Kink 13.9: Challenges with Erections AKA when Penises Misbehave 13.10: Premature Ejaculation 13.11: Natural Physiological Changes with Aging 13.12: What are some health benefits of sexual activity? 13.13: Conclusion 13.14: Discussion Questions 13.15: For Further Exploration 13.16: Professional Associations for Sexual Health 13.17: Glossary 13.18: References Thumbnail: Petty Officer 2nd Class Nathaniel Moger 2008. Public domain


3.24: Resonant scattering
The elementary theory of the scattering of X-rays by atoms, leading to the real atomic scattering factor f o , applies only for X-radiation whose wavelength is far removed from that of any natural (resonant) frequency of the atom. When this condition does not hold, one needs to use as physical model for the scattering that of a forced damped harmonic oscillator. This leads to resonant-scattering terms in the full, now complex, scattering factor of an atom, represented by:-
\(f=f_o + f\,' + if\,''\) .
The real and imaginary terms, \(f\,', f\,''\), in the atomic scattering factor are independent of sin(θ)/λ and in general small compared to f o . The values of \(f\,'\) and \(f\,''\) change most at the absorption edge of the element in question.
In the older literature the term anomalous dispersion was used for resonant scattering. In macromolecular crystallography the term anomalous scattering is used widely in place of resonant scattering.
History
The resonant scattering of X-rays was theoretically predicted by Waller (Waller, I., 1928, Über eine verallgemeinerte Streuungsformel . Z. Phys. 51 , 213-231.) and first calculated by Hönl (Hönl, H., 1933, Zur Dispersionstheorie der Röntgenstrahlen . Z. Phys. 84 , 1-16; Hönl, H., 1933, Atomfactor für Röntgenstrahlen als Problem der Dispersionstheorie (K-Schale) . Ann. Phys. (Leipzig), 18 , 625-657.


10.3: Wounds
Phases of Wound Healing
When skin is injured, there are four phases of wound healing that take place: hemostasis, inflammatory, proliferative, and maturation. See Figure 10.10 [1] for an illustration of wound healing demonstrating hemostasis/inflammation, proliferation, and maturation.
To illustrate the phases of wound healing, imagine that you accidentally cut your finger with a knife as you were slicing an apple for a snack. Immediately after the injury occurs, blood vessels constrict and clotting factors are activated. This is referred to as the hemostasis phase . Clotting factors are released to form clots and to stop the bleeding. Platelets release growth factors that alert various cells to start the repair process at the wound location. The hemostasis phase lasts up to 60 minutes, depending on the severity of the injury. [2] , [3]
After the hemostasis phase, the inflammatory phase begins. Vasodilation occurs so that white blood cells in the bloodstream can move to the location of the wound and start cleaning the wound bed. The inflammatory process appears as edema (swelling), erythema (redness), and exudate. Exudate is fluid that oozes out of a wound and is commonly called pus or drainage. [4] , [5]
The proliferative phase of wound healing begins within a few days after the injury and includes four important processes: epithelialization, angiogenesis, collagen formation, and contraction. Epithelialization refers to the development of new epidermis and granulation tissue. Granulation tissue is new connective tissue with new, fragile, thin-walled capillaries. Collagen is also formed to provide strength and integrity to the wound. At the end of the proliferation phase, the wound begins to contract in size. [6] , [7]
Capillaries begin to develop within the wound 24 hours after injury during a process called angiogenesis . These capillaries bring more oxygen and nutrients to the wound for healing. When performing dressing changes, it is essential for the nurse to protect this granulation tissue and the associated new capillaries. Healthy granulation tissue appears pink due to the new capillary formation. It is moist, painless to the touch, and may appear “bumpy.” Conversely, unhealthy granulation tissue is dark red and painful. It bleeds easily with minimal contact and may be covered by shiny white or yellow fibrous tissue, referred to as biofilm, that must be removed because it impedes healing. Unhealthy granulation tissue is often caused by an infection, so wound cultures should be obtained when infection is suspected. [8]
During the maturation phase , collagen continues to be created to strengthen the wound. Collagen contributes strength to the wound to prevent it from reopening. A wound typically heals within 4-5 weeks and often leaves behind a scar. The scar tissue is initially firm, red, and slightly raised from the excess collagen deposition. Over time, the scar begins to soften, flatten, and become pale in about nine months. [9] , [10]
Types of Wound Healing
There are three types of wound healing: primary intention, secondary intention, and tertiary intention. Healing by primary intention means that the wound is sutured, stapled, glued, or otherwise closed so the wound heals beneath the closure. This type of healing occurs with clean-edged lacerations or surgical incisions, and the closed edges are referred to as approximated. See Figure 10.11 [11] for an image of a surgical wound healing by primary intention with approximated edges .
Secondary intention occurs when the edges of a wound cannot be approximated (brought together), so the wound heals by filling in from the bottom up with the production of granulation tissue. Examples of common wounds that heal by secondary intention are pressure injuries and skin tears. Wounds that heal by secondary infection are at higher risk for infection and must be protected from contamination. See Figure 10.12 [12] for an image of a wound healing by secondary intention.
Tertiary intention refers to the healing of a wound that has had to remain open or has been reopened, often due to severe infection. The wound is typically closed at a later date when infection has resolved. Wounds that heal by secondary and tertiary intention have delayed healing times and increased scar tissue.
Types of Wounds
There are many common types of wounds that nurses care for, such as skin tears, venous ulcers, arterial ulcers, diabetic ulcers, and pressure injuries.
Read more about different types of wounds and in the “ Wound Care ” chapter in Open RN Nursing Skills .
Wound Care
Wound care includes assessing and cleansing wounds, performing dressing changes, and implementing interventions to promote wound healing. Assessing wounds and implementing interventions to promote wound healing are further discussed in the “ Applying the Nursing Process ” section later in this chapter.
See the “ Wound Care ” chapter in Open RN Nursing Skills for additional information about cleansing wounds and performing dressing changes.
- “ 417 Tissue Repair.jpg ” by OpenStax is licensed under CC BY 3.0 . Access for free at https://openstax.org/books/anatomy-and-physiology/pages/1-introduction ↵
- This work is a derivative of Clinical Procedures for Safer Patient Care by British Columbia Institute of Technology and licensed under CC BY 4.0 ↵
- This work is a derivative of StatPearls by Grubbs & Manna and is licensed under CC BY 4.0 ↵
- This work is a derivative of Clinical Procedures for Safer Patient Care by British Columbia Institute of Technology and licensed under CC BY 4.0 ↵
- This work is a derivative of StatPearls by Grubbs & Manna and is licensed under CC BY 4.0 ↵
- This work is a derivative of Clinical Procedures for Safer Patient Care by British Columbia Institute of Technology and licensed under CC BY 4.0 ↵
- This work is a derivative of StatPearls by Grubbs & Manna and is licensed under CC BY 4.0 ↵
- McKay, M. (1990). The dermatologic history. In Walker, H. K., Hall, W. D., Hurst, J. W. (Eds.), Clinical methods: The history, physical, and laboratory examinations (3rd ed.). https://www.ncbi.nlm.nih.gov/books/NBK207/ ↵
- This work is a derivative of Clinical Procedures for Safer Patient Care by British Columbia Institute of Technology and licensed under CC BY 4.0 ↵
- This work is a derivative of StatPearls by Grubbs & Manna and is licensed under CC BY 4.0 ↵
- “ Ventriculoperitoneal shunt - surgical wound healing - belly - day 12.jpg ” by Hansmuller is licensed under CC BY-SA 4.0 ↵
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7.3: Consumption
Consumption is defined as the use of a food, good, material, or service, while a consumer can be defined as the person or entity that uses the product. Most anthropologists agree on the fact that consumption is the third subdivided phase of economic activity, the first two being production and distribution. It has been suggested that the priorities of consumption determine the production and exchange patterns, not the other way around. There are two types of consumption: personalized consumption is knowing the person who produces the goods to meet your needs, and depersonalized consumption is when a vaguely understood global system produces goods that meet your needs. There is also the difference in market and non-market based consumption. A market based consumption creates perceived needs and wants for what the market has to offer. A non-market based consumption targets satisfying minimum needs or requirements for survival.
Some economists define consumption much more broadly, as the aggregate of all economic activity that does not entail the design, production and marketing of goods and services (e.g. "the selection, adoption, use, disposal and recycling of goods and services").[11] America is the world's largest consumer in regards to an individual's consumption rates. In fact the world’s richest 20% account for 76.6% of total private consumption, while the poorest 20% account for 1.5% of total private consumption.[18] These statistics clearly indicate that wealthier individuals have more disposable income, allowing them to consume in larger volumes.
Ecology and consumption
Ecology is defined as the way a species can correspond to each other and their surroundings. These surroundings are separated into different ecozones that represent the different plants and animals that live in the area. To adapt to an ecozone, species have to create an econiche . These are the plants and animals that the species live on. People called socioecologists are the ones that study and explore the ecozones. They try to clarify why animals act the way they do in each different environment. An example would be how deer from different area act differently than others, especially the group that lives near humans.
"Cultural ecology", a section of consumption ecology, is where anthropologists try to use socioecology to explain humans within their societies. The cultural ecologists can find patterns within humans and their consumption along with the production and distribution. These can be explained through the attributes of the ecozones they live in. All humans need to learn to use the different resources that are accessible in their ecozone in order to survive. Ecology is directly related to consumption in that the ecology of different species affects the consumption of that species. So, different species and even humans in different areas consume differently depending on where they are or where they are from.
A form of agriculture known as agroecolgy implements the ideals of ecology into the science of agriculture. They prioritize keeping the process of growing and producing as natural as possible. This, however, doesn't mean that an agrocologist wants to remove all technology from agriculture, but rather an balance of technology. This would mean using technology, yet still preserving the natural process of growth. By understanding that there is no one true way to grow agriculture, agroecology allows for context based solutions, varying widely. This has led to disputes among agroecologists over what the real meaning of agroecology is.
Agroecology is partly responsible for the recent boom in popularity for sustainable agriculture. This accounts for naturally grown food, organic food, and locally grown food, all focusing on environmental health, and economic productivity. The rise of sustainable agriculture started in the past few decades, with many farmer's markets arising in towns, supporting suburban areas with food while also supporting local farmers. Also, with the prominence of industrial agriculture in modern society, people wanted an alternative to genetically modified foods. While sustainable agriculture has gotten more attention in the last decade, the agriculture sector is still the most energy hungry sector in the world. Farming will not be able to support our population if our food production does not double up by the time of 2050.
Why Do People Consume What They Do?
Consumption is usually referred to as the using up of material goods, and materials necessary for human survival. At a minimum these goods are food, drink, clothing, and shelter. Anthropologists have typically dismissed the study of consumption saying that there are no interesting questions to be asked about it. Even though this consumption of goods is the main drive of economy, it may not be in anthropologists' best interest to study it. The reasons for consumption are simple: either people need something—food and drink—or they want something—like material possessions. Both of these, they thought, weren’t likely to reveal any interesting patterns. However, for the few anthropologists who did look at consumption across different cultures, they found distinct patterns in the way humans consume.
One approach they have taken to try and understand these patters is the Internal Explanation. This explanation comes from the work done by Bronislaw Malinowski. He believed that every social practice a society had was done to support the basic human needs. Malinowski said that basic human needs could be biological or psychological. He proposed them to be nourishment, reproduction, bodily comforts, safety, movement, growth, and health. In order to satisfy each human needs proposed, corresponding practice such as food-gathering techniques, kinship, shelter, etc are essential.
The last key point in Malinowski’s explanation was that humans are solely dependent on the physical world to survive. Even though westerners see the way more primitive cultures utilize the physical world as bizarre, they are still using the same physical world we are using, just in different ways. Unfortunately, Malinowski’s explanation falls short because it doesn’t explain why all societies don’t share the same consumption patterns and why some people eat wild berries and some eat processed wheat. Cultural ecology, the study of human adaptations to social and physical environments takes over and explains why these differences exist.
Product consumption is also associated with social norms and values. If society is saying that in order to be happy, you need this, then people will follow suit and buy the product. People want to have it all and be happy, and so they willingly put their trust in the social media telling them what to buy. On the other hand, in rural areas, people consume what the social norm is. If a woman in a rural area has the norm of extravagant beads and dresses, then that is what they will get or make. Also to get people to buy products in certain areas companies will market their products to the people they want to sell their product to. They will often include the people they are marketing to in their marketing to get people to think that they are more included. For example kids cereal brands include kids eating their cereal. It is often happy children and they love the cereal. This often makes children who see the ad want to eat the cereal and ask their parents for it.