Courses 1 Calendar 2 3 Inbox 4 O History 3 10 points Produce a regression table...

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Courses 1 Calendar 2 3 Inbox 4 O History 3 10 points Produce a regression table that shows the results of each of the regressions from questions 1 and 2, along with the number of observations and the r-squared. I recommend making this table in separate software, saving it as an image, and then uploading the image in the text editor below. You may also create a table inside the text editor itself, but this is harder to make look good, and you are at higher risk of losing your work. BIVA I E 12pt . Studio Paragraph Resources Return Submit 10 points Download and open the "House ElectionsSpending 2018.csv" dataset and the associated "README.txt", which describes the files in the dataset. We want to study how campaign spending by challengers and incumbents affects incumbent vote share. For this, we will need to transform some of the variables so we have a measure of incumbent vote share, as well as incumbent and challenger spending. So before you start answering the questions below, create a new variable for each of these. The easiest way to do this in Excel is to use the "IF" function B. For example, to create a variable for incumbent vote share, use the IF statement to populate the new variable (you could call it "incvoteshare") with "repvoteshare" if "incumbent" is R, and 1-"repvoteshare" if "incumbent" is not R. You will probably want to use the formula builder in Excel to do this, and the resulting command in row 2 (as an example) might look like this: "=IF(C2=("R"),D2,1-D2)"). Once you have created one cell like this, you can complete the remaining column by clicking on the bottom right corner of the completed cell and dragging the mouse down. This will auto- populate the same formula into the rest of your rows. a) Run a regression of incumbent vote share (your dependent variable) on both incumbent spending and challenger spending. Report the coefficients and their standard errors. (Refer back to the method you used in the "Regression" worksheet.) b) Note that if challenger spending is positively correlated with higher challenger vote shares, it must be negatively correlated with incumbent vote share. In light of this, how should we interpret the estimated coefficients associated with your independent variables? +4 12pt BIUA Paragraph 4 A EX X E E Courses 1 Calendar 2 3 Inbox 4 O History 3 10 points Produce a regression table that shows the results of each of the regressions from questions 1 and 2, along with the number of observations and the r-squared. I recommend making this table in separate software, saving it as an image, and then uploading the image in the text editor below. You may also create a table inside the text editor itself, but this is harder to make look good, and you are at higher risk of losing your work. BIVA I E 12pt . Studio Paragraph Resources Return Submit 10 points Download and open the "House ElectionsSpending 2018.csv" dataset and the associated "README.txt", which describes the files in the dataset. We want to study how campaign spending by challengers and incumbents affects incumbent vote share. For this, we will need to transform some of the variables so we have a measure of incumbent vote share, as well as incumbent and challenger spending. So before you start answering the questions below, create a new variable for each of these. The easiest way to do this in Excel is to use the "IF" function B. For example, to create a variable for incumbent vote share, use the IF statement to populate the new variable (you could call it "incvoteshare") with "repvoteshare" if "incumbent" is R, and 1-"repvoteshare" if "incumbent" is not R. You will probably want to use the formula builder in Excel to do this, and the resulting command in row 2 (as an example) might look like this: "=IF(C2=("R"),D2,1-D2)"). Once you have created one cell like this, you can complete the remaining column by clicking on the bottom right corner of the completed cell and dragging the mouse down. This will auto- populate the same formula into the rest of your rows. a) Run a regression of incumbent vote share (your dependent variable) on both incumbent spending and challenger spending. Report the coefficients and their standard errors. (Refer back to the method you used in the "Regression" worksheet.) b) Note that if challenger spending is positively correlated with higher challenger vote shares, it must be negatively correlated with incumbent vote share. In light of this, how should we interpret the estimated coefficients associated with your independent variables? +4 12pt BIUA Paragraph 4 A EX X E E