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Basic Question 2 of 11
Statisticians use the central limit theorem when studying sampling distributions because ______
B. the shape of the population is not important when the sample size is greater than 30.
C. the shape of the sample distribution is not important when the population size is greater than 30.
D. the shape of the population distribution is important when the sample size is less than 30.
A. the size of the sample is not important when the population is approximately normally distributed.
B. the shape of the population is not important when the sample size is greater than 30.
C. the shape of the sample distribution is not important when the population size is greater than 30.
D. the shape of the population distribution is important when the sample size is less than 30.
User Contributed Comments 7
| User | Comment |
|---|---|
| Gina | shape of the population distribution... vs shape of the population? |
| vincenthuang | what's the differece between B and D From the LOS " No matter what the shape of the orginal distribution" seems like D is close. |
| minna | the central limit theorem does not say anything about sample size smaller than 30. So D is incorrect. |
| nufan | It is not because it is true that it answer why statisticians use the Central Limit Theorem (..) . |
| amamed213 | why not A ? |
| Jurrens | it's not A bc the size of the sample is still important. |
| johntan1979 | No, A is correct but not the answer to why statisticians use CLT. |
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Learning Outcome Statements
explain the central limit theorem and its importance for the distribution and standard error of the sample mean
CFA® 2024 Level I Curriculum, Volume 1, Module 7.