You run a regression of Iowa crop yield per acre on average growing season temperature, average growing season rainfall, and average growing season total precipitation. You get the following results:

What problem(s) do you think this regression has?

a) Ommitted variable of how much fertilizer was used. This will impact the Rain coefficient.

b) Multi-collinearity. Rain and precipitation are very highly correlated, their estimates are unreliable.

c) Huge outliers are driving the result from years in drought.

d) No issues, regression is probably fine.

Question 2

You run a regression of grades on a final exam on time spend studying and get the regression equation:

Grade = 94 - 6.2 * Hours_Spent_Studying + error

What is your takeaway from this regression?

a) Studying is bad, and causes worse grades.

b) Students don't know how to study very well

c) A few outliers are skewing the results

d) Students who are less confident study more, but still do worse. There is an omitted variable skewing the results.

Question 3:

You plot the residuals from a regression and get this plot. What do you see as a problem?

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