The central limit theorem states that
A)the sampling distribution of $\frac { \bar { Y } - \mu _ {y} } { \sigma \bar { Y } }$ is approximately normal.
B) $\bar { Y } \xrightarrow{p} \mu _ { \gamma }$
C)the probability that $\bar { Y }$ is in the range $\mu_y$ ± c becomes arbitrarily close to one as n increases for any constant c 0.
D)the t distribution converges to the F distribution for approximately n 30.

Question

The central limit theorem states that
A)the sampling distribution of $\frac { \bar { Y } - \mu _ {y} } { \sigma \bar { Y } }$ is approximately normal.
B) $\bar { Y } \xrightarrow{p} \mu _ { \gamma }$
C)the probability that $\bar { Y }$ is in the range $\mu_y$ ± c becomes arbitrarily close to one as n increases for any constant c > 0.
D)the t distribution converges to the F distribution for approximately n > 30.

Quizplus · Accepted Answer

The central limit theorem states that the sampling distribution of the sample mean $\bar{Y}$ approaches a normal distribution as the sample size n becomes large, regardless of the shape of the population distribution.

The Central Limit Theorem States That A)the Sampling Distribution Of \frac

The Central Limit Theorem States That
A)the Sampling Distribution Of \frac