AP Statistics Inference Review

Front

What is a Type I error in hypothesis testing?

Back

A Type I error occurs when the null hypothesis is rejected when it is actually true.

Front

What is a Type II error in hypothesis testing?

Back

A Type II error occurs when the null hypothesis is not rejected when it is actually false.

Front

How can increasing the sample size affect Type I and Type II errors?

Back

Increasing the sample size can reduce the probability of both Type I and Type II errors.

Front

What is a test statistic?

Back

A test statistic is a standardized value that is calculated from sample data during a hypothesis test.

Front

What does a negative test statistic indicate?

Back

A negative test statistic indicates that the sample mean is less than the hypothesized population mean.

Front

What is a confidence interval?

Back

A confidence interval is a range of values used to estimate the true parameter of a population, with a specified level of confidence.

Front

What does a 95% confidence interval mean?

Back

A 95% confidence interval means that if we were to take many samples and build intervals, approximately 95% of those intervals would contain the true population parameter.

Front

What is the formula for calculating a confidence interval for a mean?

Back

Confidence Interval = sample mean ± (critical value * standard error)

Front

What is the standard error?

Back

The standard error is the standard deviation of the sampling distribution of a statistic, commonly the mean.

Front

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

Back

A one-sample t-test compares the mean of a single sample to a known value, while a two-sample t-test compares the means of two independent samples.