# Hi just need some help with questions c, d and e. This are the solutions for parts A and B which …

**Hi just need some help with questions c, d and e. This are the solutions for parts A and B which will be needed for solving c, d and e, Thanks very much in advance. (NOW UPDATED) Sorry**

Part A and B regression:

The variables are defined as follows:

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Order Paper Now*voteA* = percentage 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)

*prtystrA* =a measure of party strength for candidate A (the fraction of the most recent presidential vote that went to Aâ€™s party, expressed in percent)

**A) What is the interpretation of the coefficients? Are the slope coefficients individually significant? (Note: use a significance level of 5 percent).**

Coefficient of EXPENDA shows that there is a negative relationshipe between percentage of votes recieved by A and expenditure on campaign by A. if EXPENDA increases by 1 unit percentage of votes received by A decreases by 1.28 units.

Coefficient of EXPENDB shows that there is a negative relationship between percentage of votes recieved by A and expenditure on campaign by B. If EXPENDB increases by 1 unit percentage of votes received by A decreases by 2.91.

Coeffcient of PRTYSTRA shows that there is a posiitve relationship between percentage of votes received by A and measure of party strength for A. If party strength increases by 1 unit, percentage of votes received by A increases by 0.09 units.

Coefficient is significant if its absolute t statistic is greater than critical t statistic of 1.96. Only EXPENDB has t statistic greater than 1.96. So only EXPENDB is statistically significant.

**B) We are interested in conducting a joint significance test on expendA and prtystrA. Write down the null and alternative hypotheses of this test. What are the degrees of freedom associated with this test?**

let coefficient of expendA be b2 and coefficient of prtystraA be b3.

H0: b2=b3=0

H1: b2 not equal to b3 not equal to 0

degrees of freedom for numerator is 2 which is the number of restriction.

degrees of freedom for denominator is n-k-1 where n is 40, k is the no. of explanatory variables which is 3. degrees of freedom for denominator is 40-3-1= 36.

multiple regression generates the following result: Dependent Variable: VOTEA Method: Least Squares Date: 03/15/18 Time: 17:23 Sample: 1 40 Included observations: 40 Variable Coefficient Std. Error t-Statistic Prob EXPENDA EXPENDB PRTYSTRA 80.47166 9.2232278.7248920.0000 1.276232 .466541 -0.870233 0.3899 2.9076940.540867-5.375989 0.0000 0.093120 0.081806 1.138293 0.2625 R-squared Adjusted R-squared S.E. of regression Sum squared resid Log likelihood F-statistic Prob(F-statistic) 0.593406 0.559523 4.923050 872.5111 Mean dependent var S.D. dependent var Akaike info criterion Schwarz criterion 66.05000 7.417754 6.120373 6.289261 6.181438 2.051466 -118.4075 Hannan-Quinn criter 17.51343 Durbin-Watson stat 0.000000

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