Lesson 2.02c

2.02c Bivariate data Quiz: OCR Maths, Unit 12

20 questions

Written by Revision Ninja · Last reviewed 11 October 2026

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Lesson 2.02c, Bivariate data: 20 multiple choice questions for the OCR Maths (H240), Unit 12: Data Presentation and Interpretation, written with Revision Ninja.

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The 20 questions

  1. What describes a positive correlation between two variables on a scatter diagram?

    • One increases one decreases
    • Both remain constant
    • Both increase together
    • No pattern exists

  2. Why does strong correlation between two variables not prove that one causes the other?

    • Third factor acting
    • Data always invalid
    • Variables independent
    • Correlation purely random

  3. What is the main practical use of a linear regression line?

    • Proving causal relationships
    • Identifying outlier limits
    • Calculating exact probabilities
    • Predicting dependent values

  4. What do distinct clusters on a scatter diagram suggest about a population?

    • Strong linear correlation
    • Distinct sub-populations
    • Perfect causation
    • Uniform distribution

  5. How are data points arranged on a scatter diagram showing weak negative correlation?

    • Loosely spread upwards
    • Loosely spread downwards
    • Tightly clustered upwards
    • Tightly clustered downwards

  6. What is the process of predicting values outside the range of given data called?

    • Interpolation
    • Correlation
    • Regression
    • Extrapolation

  7. Which variable is conventionally plotted on the horizontal x-axis of a scatter diagram?

    • Extrapolated variable
    • Dependent variable
    • Response variable
    • Explanatory variable

  8. What does a strong positive correlation between ice cream sales and temperature demonstrate?

    • Direct causation
    • Association, not causation
    • Zero correlation
    • Inverse proportion

  9. A regression line is y = 2x + 3. What is the predicted y when x = 10?

    • 13
    • 23
    • 20
    • 32

  10. Using a model fitted for x between 0 and 20 to estimate y at x = 50 is called what?

    • Extrapolation
    • Integration
    • Interpolation
    • Standardisation

  11. If a scatter diagram shows two separate clusters, how should regression lines be fitted?

    • Fit lines separately
    • Fit one line
    • Fit horizontal line
    • Ignore both clusters

  12. What layout of points on a scatter diagram indicates strong negative correlation?

    • Tight downward trend
    • Loose upward trend
    • Random scattered points
    • Tight upward trend

  13. A correlation of 0.8 between study hours and exam scores indicates what type of relationship?

    • No linear relationship
    • Weak negative association
    • Strong positive association
    • Definite direct causation

  14. On a scatter diagram, what is a single point far from the rest called?

    • A cluster
    • An outlier
    • The median point
    • A residual of zero

  15. Shoe size and reading ability in children are positively correlated. What is the most likely lurking variable?

    • Age
    • Shoe size
    • Reading ability
    • Gender

  16. If all data points lie exactly on a line with a positive gradient, what is the correlation?

    • Strong negative correlation
    • Weak positive correlation
    • Perfect positive correlation
    • Zero correlation

  17. Why is fitting a single regression line to data with distinct sections inappropriate?

    • Requires more data
    • Forces negative gradient
    • Misrepresents distinct groups
    • Calculates zero correlation

  18. What type of relationship can still exist between two variables if linear correlation is zero?

    • Perfect correlation
    • Strong linear relationship
    • Direct causation
    • Non-linear relationship

  19. Why does a high correlation between fire engines and fire damage not prove causation?

    • Extrapolation occurred
    • Sample too large
    • Correlation is negative
    • Lurking variables exist

  20. What is the main drawback of fitting one regression line across two separated clusters?

    • Poor overall fit
    • Guarantees perfect accuracy
    • Changes data values
    • Always zero gradient

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