Sampling Distributions

Front

What is a sampling distribution?

Back

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

Front

What does the Central Limit Theorem state?

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

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 is the standard deviation of a sampling distribution called?

Back

The standard deviation of a sampling distribution is called the standard error.

Front

How is the standard error calculated?

Back

The standard error is calculated by dividing the population standard deviation by the square root of the sample size (n).

Front

What happens to the standard error as the sample size increases?

Back

As the sample size increases, the standard error decreases.

Front

What is the relationship between sample size and the shape of the sampling distribution?

Back

As the sample size increases, the shape of the sampling distribution becomes narrower and more normal.

Front

What symbols represent the mean and standard deviation of a sample?

Back

The mean is represented by x̄ (x-bar) and the standard deviation by s.

Front

What symbols represent the mean and standard deviation of a population?

Back

The mean is represented by μ (mu) and the standard deviation by σ (sigma).

Front

What symbols represent the mean and standard deviation of a sampling distribution?

Back

The mean is represented by μ (mu) and the standard deviation by σ/√n.