Question 2
3.Consider the data set scores on a class of 98 students in IIT-M. For each of 98 students, the composite score obtained in the class and the average number of hours studied per week is recorded. The following regression output was obtained using the scores data set
Call:lm(formula = score ~ hours)
Residuals: Min 1Q Median 3Q Max-39.680 -14.675 0.215 14.088 54.785
Coefficients: Estimate Std. Error t value Pr(>|t|)(Intercept) 7.8805 4.6247 1.704 0.0916 .hours 7.1852 0.6134 11.713 <2e-16 ***---Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 20.08 on 96 degrees of freedomMultiple R-squared: 0.5883, Adjusted R-squared: 0.584F-statistic: 137.2 on 1 and 96 DF, p-value: < 2.2e-16For the following questions, please explain clearly which parts of the output are the basis for your answers. Include the units of variables wherever possible. Use the tabulated values in the cheat sheet.
(a) What is the predictor variable? What is the response variable? [2 Marks]
(b) Write the equation for the estimated conditional mean function, using the appropriate numerical values in the output. [2 Marks]
(c) Based on the estimated coefficients, can you give an estimate of ? If yes, what is it (and show your work); if not, explain why not (missing information, inappropriate assumptions, etc.). [3 Marks]
(d) Give a 95% confidence interval for , assuming all the model assumptions hold. [2 Marks]
(e) What is , the in-sample mean-squared error? [3 Marks]
(f) From , the standard error of and , can you find the sample variance in population across cities? If so, what is it? If not, explain. [5 Marks]
(g) Which part (or parts) of the output (if any) tests the assumption that the relationship between the predictor variable and the response variable is linear? [5 Marks]
I have written answers on the answer sheets
Not applicable