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The estimated regression equation for a model involving two independent variables and 10 observations follows. ý = 24.1370 + 0.5704x_ + 0.4950X2 (a) Interpret b, in this estimated regression equation. Ob₁ = 24.1370 is an estimate of the change in y corresponding to a 1 unit change in x₁ when x₂ is held constant. O b₁ = 0.4950 is an estimate of the change in y corresponding to a 1 unit change in x₂ when x₁ is held constant. Ob₁: = 0.4950 is an estimate of the change in y corresponding to a 1 unit change in x₁ when x₂ is held constant. Ob₁ = 0.5704 is an estimate of the change in y corresponding to a 1 unit change in x₂ when x₁ is held constant. O b₁ = 0.5704 is an estimate of the change in y corresponding to a 1 unit change in x₁ when x₂ is held constant. Interpret b₂ in this estimated regression equation. b₂² = 24.1370 is an estimate of the change in y corresponding to a 1 unit change in x, when x₂ is held constant. Ob₂ = 0.4950 is an estimate of the change in y corresponding to a 1 unit change in x₁ when x₂ is held constant. = 0.4950 is an estimate of the change in y corresponding to a 1 unit change in x₂ when x₁ is held constant. 0b₂ Ob₂ = 0.5704 is an estimate of the change in y corresponding to a 1 unit change in x₂ when x₁ is held constant. O b₂ = 0.5704 is an estimate of the change in y corresponding to a 1 unit change in x₁ when X₂ is held constant. (b) Predict y when x₁ = 170 and x₂ = 330.

The estimated regression equation for a model involving two independent variables and 10 observations follows. ý = 24.1370 + 0.5704x_ + 0.4950X2 (a) Interpret b, in this estimated regression equation. Ob₁ = 24.1370 is an estimate of the change in y corresponding to a 1 unit change in x₁ when x₂ is held constant. O b₁ = 0.4950 is an estimate of the change in y corresponding to a 1 unit change in x₂ when x₁ is held constant. Ob₁: = 0.4950 is an estimate of the change in y corresponding to a 1 unit change in x₁ when x₂ is held constant. Ob₁ = 0.5704 is an estimate of the change in y corresponding to a 1 unit change in x₂ when x₁ is held constant. O b₁ = 0.5704 is an estimate of the change in y corresponding to a 1 unit change in x₁ when x₂ is held constant. Interpret b₂ in this estimated regression equation. b₂² = 24.1370 is an estimate of the change in y corresponding to a 1 unit change in x, when x₂ is held constant. Ob₂ = 0.4950 is an estimate of the change in y corresponding to a 1 unit change in x₁ when x₂ is held constant. = 0.4950 is an estimate of the change in y corresponding to a 1 unit change in x₂ when x₁ is held constant. 0b₂ Ob₂ = 0.5704 is an estimate of the change in y corresponding to a 1 unit change in x₂ when x₁ is held constant. O b₂ = 0.5704 is an estimate of the change in y corresponding to a 1 unit change in x₁ when X₂ is held constant. (b) Predict y when x₁ = 170 and x₂ = 330.

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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**Estimated Regression Equation for Educational Purposes** The estimated regression equation for a model with two independent variables and 10 observations is as follows: \[ \hat{y} = 24.1370 + 0.5704x_1 + 0.4950x_2 \] **(a) Interpretation of Coefficients:** i. **Interpret \(b_1\) in this estimated regression equation:** - \(b_1 = 24.1370\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_1\) when \(x_2\) is held constant. - \(b_1 = 0.4950\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_2\) when \(x_1\) is held constant. - **\(b_1 = 0.4950\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_1\) when \(x_2\) is held constant.** - \(b_1 = 0.5704\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_2\) when \(x_1\) is held constant. - **\(b_1 = 0.5704\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_1\) when \(x_2\) is held constant.** ii. **Interpret \(b_2\) in this estimated regression equation:** - \(b_2 = 24.1370\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_1\) when \(x_2\) is held constant. - **\(b_2 = 0.4950\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_2\) when \(x_1\) is held constant.** - \(b_2 = 0.4950\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_1\) when \(x_2\
Transcribed Image Text:**Estimated Regression Equation for Educational Purposes** The estimated regression equation for a model with two independent variables and 10 observations is as follows: \[ \hat{y} = 24.1370 + 0.5704x_1 + 0.4950x_2 \] **(a) Interpretation of Coefficients:** i. **Interpret \(b_1\) in this estimated regression equation:** - \(b_1 = 24.1370\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_1\) when \(x_2\) is held constant. - \(b_1 = 0.4950\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_2\) when \(x_1\) is held constant. - **\(b_1 = 0.4950\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_1\) when \(x_2\) is held constant.** - \(b_1 = 0.5704\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_2\) when \(x_1\) is held constant. - **\(b_1 = 0.5704\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_1\) when \(x_2\) is held constant.** ii. **Interpret \(b_2\) in this estimated regression equation:** - \(b_2 = 24.1370\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_1\) when \(x_2\) is held constant. - **\(b_2 = 0.4950\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_2\) when \(x_1\) is held constant.** - \(b_2 = 0.4950\) is an estimate of the change in \(y\) corresponding to a 1-unit change in \(x_1\) when \(x_2\
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