When we want to infer from a sample to the population,what must be assumed?

A) The sample is normally distributed.
B) The sample is large.
C) The population is normally distributed.
D) The population is large.

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Elizabeth Doyle · Accepted Answer

Final Answer : C, Explanation :  To make inferences from a sample to a population, it is typically assumed that the population is normally distributed, especially when using parametric tests. This assumption allows for the application of the Central Limit Theorem, which states that the sampling distribution of the sample mean will be approximately normal if the sample size is large enough, regardless of the population's distribution.

When we want to infer from a sample to the population,what must be assumed?

A) The sample is normally distributed.
B) The sample is large.
C) The population is normally distributed.
D) The population is large.

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When we want to infer from a sample to the population,what must be assumed?A) The sample is normally distributed.B) The sample is large.C) The population is normally distributed.D) The population is large.

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Learning Objectives

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Related questions

When we want to infer from a sample to the population,what must be assumed?

A) The sample is normally distributed.
B) The sample is large.
C) The population is normally distributed.
D) The population is large.