STAT 5.5 sampling distribution

Front

What is a sampling distribution?

Back

A sampling distribution is the probability distribution of a statistic (like the sample mean or sample proportion) obtained from a large number of samples drawn from a specific population.

Front

What is the mean of a sampling distribution?

Back

The mean of a sampling distribution is equal to the mean of the population from which the samples are drawn.

Front

What happens to the variability of the sampling distribution as the sample size increases?

Back

As the sample size increases, the variability (or standard deviation) of the sampling distribution decreases.

Front

What is the standard error of the sample proportion?

Back

The standard error of the sample proportion is calculated as sqrt[(p(1-p)/n)], where p is the population proportion and n is the sample size.

Front

What is the Central Limit Theorem?

Back

The Central Limit Theorem states that the sampling distribution of the sample mean will be approximately normally distributed if the sample size is sufficiently large, regardless of the population's distribution.

Front

How does sampling with replacement differ from sampling without replacement?

Back

In sampling with replacement, each member of the population can be selected more than once, while in sampling without replacement, once a member is selected, it cannot be chosen again.

Front

What is the effect of reducing sample size on the variance of the sampling distribution?

Back

Reducing the sample size increases the variance of the sampling distribution.

Front

What is a sample proportion?

Back

A sample proportion is the ratio of the number of successes in a sample to the total number of observations in that sample.

Front

What is the formula for calculating the standard deviation of the sampling distribution of a sample proportion?

Back

The formula is sqrt[(p(1-p)/n)], where p is the sample proportion and n is the sample size.

Front

What does it mean if a sampling distribution is skewed?

Back

If a sampling distribution is skewed, it means that the distribution is not symmetrical and has a longer tail on one side than the other.