Q.Explain the meaning of regression and state two differences between correlation and regression.
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 on and the regression of on — each represented by a straight line of best fit.
Differences between correlation and regression:
| Feature | Correlation | Regression |
|---|---|---|
| Purpose | Measures whether and how strongly two variables are related | Estimates the value of one variable from the other |
| Result | A single unit-free number | An equation (line) with a coefficient |
| Symmetry | Symmetric: | Not symmetric: in general |
| Variables | No distinction between the two | Distinguishes dependent and independent variable |
(Any two of these differences earn full marks.)
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 .
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