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Two-Variable Data Checkpoint

A free Statistics and Data Analysis lesson from the “Two-Variable Data” unit, with a worked example and practice problems including step-by-step solutions.

This checkpoint reviews two-way tables, conditional relative frequency, scatter plots, regression lines, residuals, and prediction limits.

What you'll learn

Why it matters: Statistics assessments mix computation with interpretation, just like real reports: the numbers matter, but the conclusion has to match the context and the study design.

Worked example

Problem. A scatter plot with points rising left to right shows:

  1. When x increases and y tends to increase, the direction is positive.
  2. That is positive association.

Answer: positive association

Lesson preview: this page shows 5 practice items. The interactive activity contains 25 practice items and 25 quiz items (multiple choice and typed response). Counts include repeated prompts and variants.

Practice problems

1. Review case A: A scatter plot with points rising left to right shows:

Choices: negative association · no association · a categorical variable only · positive association

Show solution
  1. When x increases and y tends to increase, the direction is positive.
  2. That is positive association.

Answer: positive association

2. Review case B: Correlation by itself can prove:

Choices: association, not causation · cause and effect every time · that the sample was random · that there are no outliers

Show solution
  1. Correlation measures association.
  2. It does not prove causation without a stronger design.

Answer: association, not causation

3. Review case C: A regression line is y = 5x + 8. Predict y when x = 4.

Show solution
  1. Substitute x = 4.
  2. 5(4) + 8 = 28.

Answer: 28

4. Review case D: A model predicts 19, but the actual value is 21. Find the residual using actual - predicted.

Show solution
  1. Residual = actual - predicted.
  2. 21 - 19 = 2.

Answer: 2

5. Review case E: Predicting inside the observed x-range is called:

Choices: extrapolation · random assignment · standard error · interpolation

Show solution
  1. Interpolation stays inside the data range.
  2. Extrapolation goes beyond the observed data.

Answer: interpolation

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