Question

In an earlier tutorial, you were introduced to a data set that contains voting information for 173 US election districts. Suppose we have access to 40 observations from that data set. Throughout this assignment, data analysis is conducted on these 40 observations only The variables are defined as folloWS: xotedpercentage of the vote received by Candidate A expendA-campaign expenditure by Candidate A (in million dollars) expendB-campaign expenditure by Candidate B (in million dollars) grtvstra -a measure of party strength for candidate A (the fraction of the most recent presidential vote that went to A's party, expressed in percent) A multiple regression generates the following result: Dependent Variable: VOTEA Method: Least Squares Date: 0315/18 Time: 17:23 Sample: 1 40 Included obs ervations:40 Varia ble Coefficient Std. Error Statistic Prob 80.47188 9.223227 8.724892 0.0000 1278232 1.488541 -0870233 0.3899 2.907694 0.540867 -5.375989 0.0000 0.093120 0.081808 1138293 0.28625 EXPENDB PRTYSTRA R-s quared Adjus ted R-s quared S.E of regres s iorn Sum s quared res id Log likelihood F-statis tic Prob/F-ststis tic) 0.593406 Mean dependent var 0.559523 S.D. dependent var 4.923050 Aake info criterion 872.5111 Schwarzcriterion 118.4075 Hannan-Quinn criter 17.51343 Durbin-Was on stat 0.000000 88.05000 7.417754 8.120373 8.289281 8.181438 2051488 (a)(1pt) What is the interpretation of the coefficients? Are the slope coefficients individually significant? (Note: use a significance level of 5 percent). (b)Xlpt) We are interested in conducting a joint significance test on expendA and grtvstrA. Write down the null and alternative hypotheses of this test. What are the degrees of freedom associated with this test?