Question

If all possible random samples of size N are drawn from a population with a mean of mu and a standard deviation of sigma, then as N becomes larger, the sampling distribution of sample means becomes approximately normal with a mean of muy(bar) and a standard deviation of sigmay(bar). This statement is known as the:

Answer 1

Answer:

"Central limit theorem" is the right answer.

Step-by-step explanation:

A hypothesis essentially claims that whenever there seems to be a small variance throughout the big confidence intervals, the sampling is based on averages as well as the sampling distribution (mean) usually nearly the same as the public's median.

When,

• Mean = $\mu_y$
• Standard deviation = $\sigma_y$
• Sample size = N

is sufficiently larger than $\bar Y \sim N(\mu_y, \sigma_y)$

Thus, the above is the right answer.