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Worked Examples · Example 1

Q.Explain the meaning of regression and state two differences between correlation and regression.

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✓ Free question

Meaning. Regression is the statistical method of estimating (predicting) the value of one variable from the known value of another variable with which it is correlated. The variable being estimated is the dependent variable and the one used to estimate is the independent variable. Since either variable can be estimated from the other, there are two regression relationships — the regression of YY on XX and the regression of XX on YY — each represented by a straight line of best fit.

Differences between correlation and regression:

FeatureCorrelationRegression
PurposeMeasures whether and how strongly two variables are relatedEstimates the value of one variable from the other
ResultA single unit-free number rrAn equation (line) with a coefficient
SymmetrySymmetric: rxy=ryxr_{xy}=r_{yx}Not symmetric: byx≠bxyb_{yx}\neq b_{xy} in general
VariablesNo distinction between the twoDistinguishes dependent and independent variable

(Any two of these differences earn full marks.)

✓Final answer

Regression is the technique of estimating one variable from a correlated other variable using a line of best fit. It differs from correlation because (i) it yields an estimating equation rather than a single number, and (ii) it is not symmetric — it separates dependent from independent variables, with byx≠bxyb_{yx}\neq b_{xy}.

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