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4.2 Regression — Test 1
Q1. Regression analysis is primarily used to:✓ Predict the value of one variable from another
Q2. In regression, the variable being predicted is called the:✓ Dependent variable
Q3. The regression line is also known as the:✓ Line of best fit
Q4. The method commonly used to fit a regression line is the:✓ Method of least squares
Q5. In the regression equation Y = a + bX, the term 'b' is the:✓ Slope (regression coefficient)
Q6. In the regression equation Y = a + bX, the term 'a' is the:✓ Intercept (value of Y when X = 0)
Q7. A key difference between correlation and regression is that regression:✓ Is directional (predicts a dependent variable), while correlation is symmetric
Q8. For a pair of variables, there are generally:✓ Two regression lines (Y on X and X on Y)
Q9. The difference between an observed value and the value predicted by the regression line is called the:✓ Residual
Q10. The sign of the regression coefficient (slope) is:✓ The same as the sign of the correlation coefficient
Q11. The coefficient of determination (r²) in regression indicates the:✓ Proportion of variation in Y explained by X
Q12. Regression is especially useful for:✓ Forecasting or estimating values of the dependent variable
Q13. The correlation coefficient r is related to the two regression coefficients as the:✓ Geometric mean of the two regression coefficients
Q14. A regression line is used to estimate Y for a given X by:✓ Substituting the X value into the regression equation
Q15. The two regression lines coincide (become one line) only when the correlation is:✓ Perfect (r = +1 or −1)
Q16. In simple linear regression, the relationship between X and Y is modelled as a:✓ Straight line
Q17. If the regression coefficient b is positive, then as X increases, Y:✓ Increases
Q18. Extrapolating a regression line far beyond the range of the observed data is:✓ Risky, because the relationship may not hold there
Q19. Compared with correlation, which describes the strength of association, regression provides:✓ A predictive equation relating the variables
Q20. Match each regression term with its description and select the correct option.✓ A-iii, B-i, C-iv, D-ii