AP Stats - Unit 4 - Hypothesis Tests: Proportions

Front

What are the null and alternative hypotheses in a significance test?

Back

Ho: parameter, Ha: parameter

Front

What is a sampling distribution?

Back

A distribution of all the values taken by a statistic from all possible samples of a given size.

Front

What effect does increasing the sample size have on the variability of estimates in an opinion poll?

Back

It reduces the variability of the estimates made from the data collected in the poll.

Front

What is the p-value in hypothesis testing?

Back

The p-value is the probability of obtaining test results at least as extreme as the results actually observed, under the assumption that the null hypothesis is correct.

Front

What is the probability of a type I error?

Back

Alpha (α), which is the probability of rejecting the null hypothesis when it is actually true.

Front

What is the difference between a parameter and a statistic?

Back

A parameter is a numerical value that summarizes a characteristic of a population, while a statistic is a numerical value that summarizes a characteristic of a sample.

Front

What does it mean if a test is statistically significant?

Back

It means that the p-value is less than the significance level (alpha), leading to the rejection of the null hypothesis.

Front

What is the significance level (alpha) in hypothesis testing?

Back

The significance level (α) is the threshold for determining whether a p-value indicates a statistically significant result.

Front

What is a type II error?

Back

A type II error occurs when the null hypothesis is not rejected when it is false (beta, β).

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.