Example 1 Remember the underlying assumptions for Linear Regression Models: ⚫ Linearity ■ No interaction between explanatory variables "best fit" equations may give counterintuitive results List all possible model specifications given the correlation coefficient table shown in the table below Y X₁ X₂ X3 X4 Y 1.00 0.32 0.92 0.95 0.62 X₁ 1.00 0.25 0.19 0.03 X2 1.00 0.99 0.29 X3 1.00 0.33 X4 1.00 32
Example 1 Remember the underlying assumptions for Linear Regression Models: ⚫ Linearity ■ No interaction between explanatory variables "best fit" equations may give counterintuitive results List all possible model specifications given the correlation coefficient table shown in the table below Y X₁ X₂ X3 X4 Y 1.00 0.32 0.92 0.95 0.62 X₁ 1.00 0.25 0.19 0.03 X2 1.00 0.99 0.29 X3 1.00 0.33 X4 1.00 32
Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018
18th Edition
ISBN:9780079039897
Author:Carter
Publisher:Carter
Chapter4: Equations Of Linear Functions
Section4.6: Regression And Median-fit Lines
Problem 5PPS
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Statistics
Transcribed Image Text:Example 1
Remember the underlying assumptions for Linear Regression Models:
⚫ Linearity
■ No interaction between explanatory variables
"best fit" equations may give counterintuitive results
List all possible model specifications given the correlation
coefficient table shown in the table below
Y
X₁
X₂
X3
X4
Y
1.00
0.32
0.92
0.95
0.62
X₁
1.00
0.25
0.19
0.03
X2
1.00
0.99
0.29
X3
1.00
0.33
X4
1.00
32
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