when the sample size increases.， the probability distribution becomes is symmetric or skewed or uniform or peaked

As the size of the sample increases, what happens to the shape of the sampling means?

When a distribution has a greater proportion of the measurements to the right of the peak value, we say that it is skewed to the left.

As the size of the sample increases, what happens to the shape of the sampling means?Select one:A. cannot be predicted in advanceB. approaches a normal distributionC. positively skewedD. negatively skewed

The skewness of the Normal distribution is ______.

According to the Central Limit Theorem, the sampling distribution of the sample mean becomes approximately normally distributed asthe standard error increasesthe population variance decreasesthe size of the population increasesthe number of  samples drawn increasesthe size of the sample increases