Confidence Intervals and Hypothesis Testing

Mr. Starnes guides AP Statistics students through practice sessions on free response inference questions. The session covers constructing and interpreting confidence intervals, applying them to sample data, and conducting significance tests. Students are encouraged to attempt questions independently before reviewing solutions. The video emphasizes the importance of checking conditions, using technology for calculations, and accurately interpreting results. The session concludes with a preview of the next topic, the investigative task.

What is the main focus of the AP daily practice session introduced by Mr. Starnes?

• Reviewing past exam papers

• Practicing multiple-choice questions

• Learning new statistical theories

• Practicing free response inference questions

What is the first step in constructing a 95% confidence interval for a population proportion?

• Perform a hypothesis test

• Check the sample size

• Define parameters and identify the inference method

• Calculate the mean

Which condition is NOT necessary to check when performing a one-sample Z interval for a proportion?

• Random data production

• Large counts condition

• 10% condition for independence

• Normality of the population distribution

What is the critical value used for a 95% confidence interval in a one-sample Z interval?

• 2.58

• 2.33

• 1.96

• 1.64

Why is it important to use a template or sentence frame when interpreting confidence intervals?

• To ensure correct wording and avoid changing the meaning

• To save time

• To impress the examiner

• To make the response longer

What is the null hypothesis in the significance test example discussed?

• The new treatment is more effective

• The standard care is more effective

• There is no difference in effectiveness between treatments

• The new treatment is less effective

Why should the 10% condition not be checked in the significance test example?

• The population is infinite

• The patients were randomly assigned, not sampled

• The data is normally distributed

• The sample size is too small

What is the significance level used by default if not specified in a hypothesis test?

• 0.15

• 0.01

• 0.05

• 0.10

What does a p-value less than the significance level indicate in hypothesis testing?

• Accept the null hypothesis

• The test is inconclusive

• Reject the null hypothesis

• Fail to reject the null hypothesis

What is the main advantage of using technology for calculations in statistical tests?

• It is required by the exam

• It is more accurate

• It reduces the risk of arithmetic errors

• It is faster