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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:

Respuesta :

Cricetus

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 = [tex]\mu_y[/tex]
  • Standard deviation = [tex]\sigma_y[/tex]
  • Sample size = N

is sufficiently larger than [tex]\bar Y \sim N(\mu_y, \sigma_y)[/tex]

Thus, the above is the right answer.

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