A government analyst tests vs. with and obtains a p-value of from a sample of . A colleague claims: "The p-value of means the probability we made a mistake is ." Which of the following explains why this statement is problematic?
AP Statistics · Unit 3 · Inference for Categorical Data: Proportions
97 AP-style multiple-choice questions and 8 free-response questions for AP Statistics · Unit 3 · Inference for Categorical Data: Proportions, sorted into 6 topics. Free sample questions for every topic.
Topic 1 of 6
a significance test for a population proportion
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An environmental scientist tests whether more than 15 percent of the water samples a factory discharges are contaminated. In a random sample of 120 discharged samples, 25 were contaminated. The test gives a statistic of 1.79 and a p-value of 0.037, and the scientist had fixed the significance level at 0.01 before collecting data. What is the correct conclusion?
Sample free-response question
A town tests samples from its water supply. Each sample is either contaminated or not. The safe standard is that at most 5 percent of samples are contaminated. The town tests H0: p = 0.05 against Ha: p > 0.05 every month.
(a) Describe a Type I error and a Type II error in this context.
(b) Which error is more serious for the town's residents? Explain.
(c) Should the town use a significance level of 0.01 or 0.10? Explain using part (b).
(d) Describe two ways the town could increase the power of its test.
(e) The test has power 0.70 if the true rate is 8 percent. Interpret this value.
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Answer, then see why
The price of gasoline rises 10% and the quantity demanded falls 5%. What happens to total revenue?
Not quite. The answer is B.
Why the other options are wrong
AI grading for free-response
Write your FRQ answer and get it scored point by point against the AP rubric, with the line from your answer that earned or missed each point.
Reason: Correctly identifies demand for gasoline as inelastic.
Evidence: "The price of gasoline rises and the quantity falls only a little."
Reason: Graph shows relatively inelastic demand.
Evidence: Draws a steep demand curve.
Reason: Correct new equilibrium price.
Evidence: Shifts supply left, P1 → P2.
Reason: With inelastic demand, a price increase raises total revenue.
Evidence: "Revenue goes down."