The file Corruption.xls contains country-level data on two variables. One of these is a measure of perceptions of political corruption. (This data is assembled by the organization Transparency.org.) [NOTE: The least corruption possible has a measure of 0, the highest a measure of 10.] The second variable is a measure of GDP per capita.

a) (10) Before looking at any data, propose a simple economic story (model) for how these two variables might be related. Write a paragraph of no less than 50 words in which you explain your argument. Which is the independent, and which is the dependent variable in your model? (Plausible stories could be told in which either variable could be the independent (or dependent) variable.)
b) (20) Whichever way you’ve chosen to model this problem, execute a linear regression. For one time in your life, you are going to be calculating the slope and intercept estimators in EXCEL (or Google Spreadsheet) using the “by hand” method that was demonstrated in the lectures. DO NOT USE THE BUILT IN EXCEL REGRESSION/VARIANCE/COVARIANCE FEATURES (except to check your work, if you desire). Report your Betahats.
c) (10) What percentage of the variation of your dependent variable is explained by the independent?
d) (10) Suppose the corruption measure was flipped. That is, the least corruption possible is rated a 10, and the highest corruption level is zero. Argentina, for instance, was originally 8, is now 2. Australia was originally 1.3, and is now 8.7. Describe how this will change the slope, intercept and R2 of your regression from above. If you can do this without recalculating the whole regression, that would be prefered

[To submit this problem, include, in order: 1) the writeup of part a; 2) a summary table that contains the important bits, like your slope, intercept, R2 terms, SST, SSE, etc…; 3) your excel spreadsheet containing your dataset and any variables or other calculations you used along the way. Try to format 3) so it doesn’t take up 20 pages. It’s OK if the spreadsheet part is small (but not invisibly small).]

Attachment:- Copy of Corrupt.S14 (1).xlsx