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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: Data Table Variable Coefficient Std. Error t value p-value (Intercept) 103.4183 42.891 2.411 0.0161 Temp 1.9446 0.0636 30.577 0.000001 Rain 43.988 21.1693 2.078 0.038 Precipitation −46.5995 21.1768 −2.2 0.028 What problem(s) do you think this regression has? Group of answer choices a) Omitted 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.

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: Data Table Variable Coefficient Std. Error t value p-value (Intercept) 103.4183 42.891 2.411 0.0161 Temp 1.9446 0.0636 30.577 0.000001 Rain 43.988 21.1693 2.078 0.038 Precipitation −46.5995 21.1768 −2.2 0.028 What problem(s) do you think this regression has? Group of answer choices a) Omitted 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.

MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
Section: Chapter Questions
Problem 1P
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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:

Data Table
Variable Coefficient Std. Error t value

p-value
(Intercept) 103.4183 42.891 2.411 0.0161
Temp 1.9446 0.0636 30.577 0.000001
Rain 43.988 21.1693 2.078 0.038
Precipitation −46.5995 21.1768 −2.2 0.028

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

Group of answer choices
a) Omitted 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.
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