7.1 Sampling Distribution

Front

What is a sampling distribution?

Back

The sampling distribution of a statistic is the distribution of values taken by the statistic in all possible samples of a given size from the population.

Front

True or False: We can use the population to make inferences about the statistic.

Back

False

Front

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

Back

The sampling distribution of any statistic will have less variability when the sample size is larger.

Front

True or False: You should always use 'The Distribution of ________' when talking about the sampling distribution.

Back

True

Front

What is the effect of increasing the sample size on precision?

Back

Increasing the sample size will result in more precision.

Front

What is the relationship between sample size and bias in sampling distributions?

Back

Increasing the sample size generally reduces bias in sampling distributions.

Front

Define 'Standard Error'.

Back

Standard Error is the standard deviation of the sampling distribution of a statistic, indicating how much the sample statistic is expected to vary from the population parameter.

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

What is the difference between a sample and a population?

Back

A population includes all members of a specified group, while a sample is a subset of the population used to make inferences about the population.

Front

What does it mean for a sample to be representative?

Back

A representative sample accurately reflects the characteristics of the population from which it is drawn.