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.
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section: Chapter Questions
Problem 4SGR
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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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