Question

Logout This preamble applies to all the remaining questions. The questions are based on the lecture example for regression with categorical data. In the lecture example, we were analyzing the association of Repair time (y), the dependent variable, with the Time since last service (X1), and the Repair type (x2). Where x2 was a dummy variable coded 1 for an electrical repair and 0 for a mechanical repair. This time we inversely coded x2 ; i.e. x2 = 1 if the repair is mechanical and x2 = 0 if the repair is electrical. With this coding of x2, we get the following regression output and the estimated regression equation for Repair times. SUMMARY OUTPUT Regression Statisties Multiple R 0.926927504 R Square 0.859194597 Adjusted R Square 0.818964482 Standard Error 0.459048301 Observations 10 ANOVA of F Significance F 21.357 0.001047533 Regression Residual Total 2 7 SS MS 9.000922601 4.5004613 1.475077399 0.210725343 10.476 Intercept X Variable 1 X Variable 2 Coefficients Standard Error Stat P-value Lower 95% 2.193188854 0.355760714 6.164786518 0.000461 1.351948442 0.387616099 0.062565187 6.195395815 0.000447 0.23967294 -1.262693498 0.314126673 4.019695257 0.005062 -2.005485048 ♡ = 2.193 +0.388X1 - 1.263x2

Answer 1

Here, no. Of observations is 10.

The degrees of freedom will be =10-2=8

Critical value of the test at alpha=0.05 with 8 degrees of freedom is 2.306.(obtained from t table)