Which graphical device is used to get a first idea of correlation between two variables?
Correct answer B. Scatter diagram
Topic / 31 questions
Correlation and Regression MCQs test the measurement of the strength and direction of a relationship between variables and the estimation of one variable from another. They help statistics students and PPSC, lecturer and UGC NET candidates. Each question gives an instant answer, so you can check key properties of r and the regression coefficients.
Correct answer B. Scatter diagram
Correct answer B. Average change in y for a unit change in x
Correct answer A. Zero
Correct answer B. byx = 1.5, bxy = 0.8
Correct answer B. Sum of squared vertical deviations of points from the line
Correct answer C. 4
Correct answer A. −0.4
Correct answer D. −1
Correct answer B. Linear relationship
Correct answer B. 0.6
Correct answer A. Sir Francis Galton
Correct answer D. 0.6
Correct answer C. 23
Correct answer D. 1.0
Correct answer A. y = 2.2 + 0.6x
Correct answer C. 0.77
Correct answer A. Perpendicular to each other
Correct answer C. They coincide
Correct answer C. (x̄, ȳ)
Correct answer C. −0.6
This Statistics topic tests short properties that are easy to state and easy to confuse. Questions ask for the range of the correlation coefficient and of the partial correlation coefficient, both from minus one to plus one, what happens to regression coefficients when r is zero, why the regression coefficients and r always have the same sign, and what follows if one regression coefficient is greater than one. You will also be asked what kind of technique regression analysis is. Learning these rules as a short list is an efficient way to secure marks in statistics papers.
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The correlation coefficient r always lies between minus one and plus one. A value of plus one shows perfect positive correlation, minus one shows perfect negative correlation, and zero shows no linear relationship. The partial correlation coefficient has the same range.
When r is zero, both regression coefficients are zero, because each coefficient equals r multiplied by a ratio of standard deviations. The two regression lines are then parallel to the axes and perpendicular to each other, showing no linear relationship.
Last reviewed October 2026