 
 <prompt> text: ```Dat median na di value wey dey separate di higher half of a data sample, population, or probability distribution, from di lower half. For a data set, you fit see am as di "middle" value. For example, for di data set {1, 3, 3, 6, 7, 8, 9}, di median na 6, di fourth largest, and also di fourth smallest, number for di sample. For a continuous probability distribution, di median na di value wey make sure say a number dey equally likely to fall above or below am.

Di median na one common measure of di properties of a data set for statistics and probability theory. Di main advantage of di median for describing data compared to di mean (wey people dey call "average") na say e no dey skewed too much by extremely large or small values, so e fit give better idea of a "typical" value. For example, for understanding statistics like household income or assets wey dey vary greatly, a mean fit dey skewed by small number of extremely high or low values. Median income, for example, fit be better way to suggest wetin a "typical" income be.

Because of dis, di median dey very important for robust statistics, as e be di most resistant statistic, wey get breakdown point of 50%: as long as no pass half of di data dey contaminated, di median no go give arbitrarily large or small result.

Answers to di questions:

1. Wetin dey very important for robust statistics?
2. Wetin be di median measure of?
3. A data set dey within wetin?
4. Wetin be di advantage of di median?
5. Skewed so much as wetin?
6. Wetin be di other helpful measure wey e fit give?
7. Wetin fit skew a mean?
8. For robust statistics, na di median be di most resistant statistic?
9. For a continuous probability distribution, how you go explain a median?
10. For a data set, how you fit describe di median?
11. For robust statistics, di median get breakdown point of wetin?
12. And e no fit get more than half of di data, wetin?
13. Wetin go happen?``` <response>: ```1. Di median.
2. Di properties of one data set.
3. Statistics and probability theory.
4. E no dey skewed too much.
5. Extremely large or small values.
6. E fit give beta idea of one "typical" value.
7. By small number of extremely high or low values.
8. Yes.
9. Di value wey one number fit equally likely to fall above or below am.
10. Di "middle" value.
11. 50%:
12. Contaminated.
13. Di median no go give one arbitrarily large or small result.``` 