The mean of the sampling distribution of the sample means according to the Central Limit Theorem is

A. exactly equal to the population mean
B. close to the population mean if the sample size is large
C. equal to the population mean divided by the square of the sample size
D. cannot be determined

Question

ChibiNyan ChibiNyan

29-05-2022
Social Studies

contestada

The mean of the sampling distribution of the sample means according to the Central Limit Theorem is

A. exactly equal to the population mean
B. close to the population mean if the sample size is large
C. equal to the population mean divided by the square of the sample size
D. cannot be determined

Respuesta :

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mboluwape mboluwape · Answer 1 · 2022-05-31T10:57:25+02:00

The mean of the sampling distribution of the sample means according to the Central Limit Theorem is exactly equal to the population mean

What is Central Limit Theorem?

Central Limit Theorem explains when as the size of a sample keep increasing the mean with become Normal in the distribution curve.

The sample become normal as the population mean becomes equal.

Therefore, The mean of the sampling distribution of the sample means according to the Central Limit Theorem is exactly equal to the population mean.

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The mean of the sampling distribution of the sample means according to the Central Limit Theorem is A. exactly equal to the population mean B. close to the population mean if the sample size is large C. equal to the population mean divided by the square of the sample size D. cannot be determined

Respuesta :

What is Central Limit Theorem?

Otras preguntas

The mean of the sampling distribution of the sample means according to the Central Limit Theorem is

A. exactly equal to the population mean
B. close to the population mean if the sample size is large
C. equal to the population mean divided by the square of the sample size
D. cannot be determined