AP Statistics chapter 9

Front

What is a p-value in hypothesis testing?

Back

A p-value is the probability of obtaining test results at least as extreme as the observed results, assuming that the null hypothesis is true.

Front

What does it mean to reject the null hypothesis?

Back

Rejecting the null hypothesis means that there is sufficient evidence to support the alternative hypothesis.

Front

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

Back

The significance level (α) is the threshold for determining whether a p-value indicates significant evidence against the null hypothesis, commonly set at 0.05.

Front

What is a Type I error?

Back

A Type I error occurs when the null hypothesis is true, but is incorrectly rejected.

Front

What is a Type II error?

Back

A Type II error occurs when the null hypothesis is false, but is incorrectly failed to be rejected.

Front

What is the purpose of a one-sample t-test?

Back

A one-sample t-test is used to determine if the mean of a single sample is significantly different from a known or hypothesized population mean.

Front

What is the difference between a one-sample z-test and a one-sample t-test?

Back

A one-sample z-test is used when the population variance is known and the sample size is large, while a one-sample t-test is used when the population variance is unknown and the sample size is small.

Front

What does it mean for a test to be statistically significant?

Back

A test is statistically significant if the p-value is less than the significance level (α), indicating strong evidence against the null hypothesis.

Front

What is the null hypothesis?

Back

The null hypothesis is a statement that there is no effect or no difference, and it serves as the default assumption in hypothesis testing.

Front

What is the alternative hypothesis?

Back

The alternative hypothesis is a statement that indicates the presence of an effect or a difference, opposing the null hypothesis.