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The following is the estimation results for a multiple linear regression model: Y=B₁ + B₁X₁ + B₂X₂ + ε SUMMARY OUTPUT Regression Statistics R-Square Regression Standard Error (S) Observations Coeff StdError 1283.000 352.000 25.228 8.631 0.861 0.372 0.558 863.100 35 t-Stat 3.65 Intercept X₁ X₂ Questions: 1. Write the fitted regression equation (30 points). 2. Write the estimated intercepts and slopes, associated with their corresponding standard errors (30 points). 3. Interpret each coefficient (40 points).

The following is the estimation results for a multiple linear regression model: Y=B₁ + B₁X₁ + B₂X₂ + ε SUMMARY OUTPUT Regression Statistics R-Square Regression Standard Error (S) Observations Coeff StdError 1283.000 352.000 25.228 8.631 0.861 0.372 0.558 863.100 35 t-Stat 3.65 Intercept X₁ X₂ Questions: 1. Write the fitted regression equation (30 points). 2. Write the estimated intercepts and slopes, associated with their corresponding standard errors (30 points). 3. Interpret each coefficient (40 points).

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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The following is the estimation results for a multiple linear regression model: Y = Bo + BX, + Bxz + 8 SUMMARY OUTPUT Regression Statistics R-Square Regression Standard Error (S) Observations 0.558 863.100 35 Coeff StdError 1283.000 352.000 25.228 8.631 0.861 0.372 t-Stat 3.65 Intercept X] X2 Questions: Write the fitted regression equation (30 points). 2 Write the estimated intercepts and slopes, associated with their corresponding standard errors (30 points). 3 Interpret each coefficient.

The following is the estimation results for a multiple linear regression model: Y=B₁ + B₁X₁ + B₂X₂ + ε SUMMARY OUTPUT Regression Statistics R-Square Regression Standard Error (S) Observations Coeff StdError 1283.000 352.000 25.228 0.861 0.558 863.100 35 8.631 0.372 t-Stat 3.65 Intercept X₁ X₂ Questions: 1. Write the fitted regression equation (30 points). 2. Write the estimated intercepts and slopes, associated with their corresponding standard errors (30 points). 3. Interpret each coefficient (40 points).
Transcribed Image Text:The following is the estimation results for a multiple linear regression model: Y=B₁ + B₁X₁ + B₂X₂ + ε SUMMARY OUTPUT Regression Statistics R-Square Regression Standard Error (S) Observations Coeff StdError 1283.000 352.000 25.228 0.861 0.558 863.100 35 8.631 0.372 t-Stat 3.65 Intercept X₁ X₂ Questions: 1. Write the fitted regression equation (30 points). 2. Write the estimated intercepts and slopes, associated with their corresponding standard errors (30 points). 3. Interpret each coefficient (40 points).
The following is the estimation results for a multiple linear regression model: Y=B₁ + B₁X₁ + B₂X₂ + ε SUMMARY OUTPUT Regression Statistics R-Square Regression Standard Error (S) Observations Coeff StdError 1283.000 352.000 25.228 0.861 0.558 863.100 35 8.631 0.372 t-Stat 3.65 Intercept X₁ X₂ Questions: 1. Write the fitted regression equation (30 points). 2. Write the estimated intercepts and slopes, associated with their corresponding standard errors (30 points). 3. Interpret each coefficient (40 points).
Transcribed Image Text:The following is the estimation results for a multiple linear regression model: Y=B₁ + B₁X₁ + B₂X₂ + ε SUMMARY OUTPUT Regression Statistics R-Square Regression Standard Error (S) Observations Coeff StdError 1283.000 352.000 25.228 0.861 0.558 863.100 35 8.631 0.372 t-Stat 3.65 Intercept X₁ X₂ Questions: 1. Write the fitted regression equation (30 points). 2. Write the estimated intercepts and slopes, associated with their corresponding standard errors (30 points). 3. Interpret each coefficient (40 points).
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