Free Correlation and Regression MCQs with Answers
30 Correlation and Regression MCQs from Quantitative Methods, each with the correct answer and a written explanation of why it is correct. Free and unlimited, with no account needed.
Correlation describes the direction and strength of association between two variables using scatter diagrams and correlation coefficients. Regression covers fitted lines, regression equations, prediction and least squares, with a clear distinction between association and causation and between estimating a response value and reversing the roles of the variables.
Last updated
30 questions · page 2 of 2
- A. Spearman's rank correlation
- B. Pearson's product-moment correlation
- C. The coefficient of variation
- D. The standard error of the mean
Explanation: Spearman's rank correlation measures association using the relative order of observations.
Correct answer: Spearman's rank correlation- A. Be multiplied by 10
- B. Remain unchanged
- C. Be divided by 10
- D. Become equal to zero
Explanation: Positive changes of measurement scale do not alter the direction or strength of linear association.
Correct answer: Remain unchanged- A. A perfect positive linear relationship
- B. No variation in either variable
- C. A strong curved relationship
- D. Exactly equal means
Explanation: Pearson's correlation measures linear association, so a strong nonlinear pattern may produce a value near zero.
Correct answer: A strong curved relationship24. Which condition is required for an ordinary least-squares regression slope to be uniquely defined?
- A. The dependent variable has zero variance
- B. The independent variable has zero variance
- C. The correlation must equal exactly one
- D. The independent variable has nonzero variance
Explanation: The slope uses the variation in the independent variable in its denominator.
Correct answer: The independent variable has nonzero variance- A. The predicted value of Y when X equals zero
- B. The change in Y for one unit of X
- C. The average error in predicting Y
- D. The correlation between X and Y
Explanation: The intercept is the fitted value of Y at X equal to zero. The slope, not the intercept, describes the expected change in Y for a one-unit…
Correct answer: The predicted value of Y when X equals zero- A. Income rises by 2.5 rupees per year
- B. Experience rises by 2.5 years per rupee
- C. Predicted income rises by 2.5 units per extra year
- D. Income and experience have correlation 2.5
Explanation: The slope gives the change in the predicted response for one unit of the explanatory variable.
Correct answer: Predicted income rises by 2.5 units per extra year- A. Its numerical value is always unit-free
- B. It must lie between zero and one
- C. Its units are units of X divided by units of Y
- D. Its units are units of Y divided by units of X
Explanation: A regression slope is a rate of change, so its units are response units per explanatory-variable unit.
Correct answer: Its units are units of Y divided by units of X- A. 6.4 percent
- B. 36 percent
- C. 64 percent
- D. 80 percent
Explanation: The coefficient of determination is the proportion of response variation explained by the regression model.
Correct answer: 64 percent- A. Always equal to one
- B. Always equal to zero when an intercept is included
- C. Always equal to the correlation coefficient
- D. Always equal to the regression slope
Explanation: When the fitted regression includes an intercept, the residuals balance so their algebraic sum is zero.
Correct answer: Always equal to zero when an intercept is included- A. This is possible in ordinary least-squares regression
- B. It proves that Y has zero variance
- C. This is impossible when both standard deviations are positive
- D. It means the intercept must be negative
Explanation: The slope for predicting Y from X equals the correlation multiplied by the ratio of the standard deviations.
Correct answer: This is impossible when both standard deviations are positive