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AP Statistics

5A–5B Day 1 Exam Practice

Shared by Ashton · Oct 20, 2026 · 4 plays

Test-style questions on describing scatterplots, interpreting r, predictions, residuals, slope and intercept, extrapolation, outliers and changing units.

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28 questions across 4 sections. After every answer you’ll see why each choice is right or wrong, not just the one you picked.

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Sample questions

Open a question to see the answer choices and the correct answer.

An agronomist models corn yield (tons per acre) from rainfall (inches) for 20 fields with ŷ = 3.42 + 0.715x. Which is the correct interpretation of the slope?
  1. A. Each extra inch of rain causes 0.715 tons/acre more yield
  2. B. Predicted yield rises 0.715 tons/acre per extra inch of rain ✓
  3. C. Predicted rainfall rises 0.715 inches per extra ton of yield
  4. D. Yield rises exactly 0.715 tons/acre per extra inch of rain

Correct answer: B. Predicted + amount + per 1 unit of x + context. That's the slope frame.

An agronomist models corn yield (tons per acre) from rainfall (inches) for 20 fields with ŷ = 3.42 + 0.715x. One field got 12 inches of rain and yielded 13.1 tons/acre. What is its residual?
  1. A. +1.1 tons/acre ✓
  2. B. −1.1 tons/acre
  3. C. +0.1 tons/acre
  4. D. +12.0 tons/acre

Correct answer: A. Ŷ = 3.42 + 0.715(12) = 12.0. Residual = 13.1 − 12.0 = +1.1: this field yielded more than predicted.

An agronomist models corn yield (tons per acre) from rainfall (inches) for 20 fields with ŷ = 3.42 + 0.715x. What does the y intercept (3.42) mean here, if anything?
  1. A. Predicted yield with 0 inches of rain, if 0 is near the data ✓
  2. B. The predicted yield at the average rainfall
  3. C. The yield increase for each additional inch of rainfall
  4. D. The average yield for all 20 fields in the study

Correct answer: A. It's the predicted y at x = 0, and it's only meaningful if 0 inches is a realistic value close to the data.

For 2001–2020, the correlation between year and North Dakota oil production is r = 0.943. A student says this proves a strong linear relationship. What's the best response?
  1. A. No, since r would need to be exactly 1 for linear
  2. B. No, since year can't be used as a variable here
  3. C. Not necessarily; a curved pattern can also have r near 1 ✓
  4. D. Yes, since any r above 0.9 shows a linear pattern

Correct answer: C. This is the slides' Alternate Example 2. The scatterplot of the oil data is clearly curved.

Across 50 cities, the number of police officers and the number of crimes have r = 0.88. Which is the most reasonable explanation?
  1. A. The correlation must be a mistake in the calculation
  2. B. A lurking variable, city population, drives both counts ✓
  3. C. More crime causes cities to need fewer police officers
  4. D. Hiring more police officers causes crime to increase

Correct answer: B. Bigger cities have more of both. Correlation doesn't imply causation.