The estimated regression equation for a model involving two independent variables and 10 observations follows. ŷ = 29.1270 + .5906x, + .4980x, a. Interpret bị and bz in this estimated regression equation. b1 Select b2 Select b. Predict y when x1 = 180 and x2 - 310 (to 2 decimals).
The estimated regression equation for a model involving two independent variables and 10 observations follows. ŷ = 29.1270 + .5906x, + .4980x, a. Interpret bị and bz in this estimated regression equation. b1 Select b2 Select b. Predict y when x1 = 180 and x2 - 310 (to 2 decimals).
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
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Chapter1: Starting With Matlab
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![### Regression Equation Analysis
The estimated regression equation for a model involving two independent variables and 10 observations is as follows:
\[ \hat{y} = 29.1270 + 0.5906x_1 + 0.4980x_2 \]
#### a. Interpret \( b_1 \) and \( b_2 \) in this estimated regression equation.
- **\( b_1 \)** represents the change in the dependent variable \( \hat{y} \) for a one-unit change in the independent variable \( x_1 \), keeping \( x_2 \) constant.
- **\( b_2 \)** represents the change in the dependent variable \( \hat{y} \) for a one-unit change in the independent variable \( x_2 \), keeping \( x_1 \) constant.
#### b. Predict \( y \) when \( x_1 = 180 \) and \( x_2 = 310 \) (to 2 decimals).
*The box is provided to input your calculated prediction based on the given values for \( x_1 \) and \( x_2 \).*](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2Ffbe4d004-b0c7-4fb9-bd84-121b248ea820%2Fb6e92ce8-3fb6-4a60-86a4-1f5dcdb5ffb2%2Fmtn729s_processed.png&w=3840&q=75)
Transcribed Image Text:### Regression Equation Analysis
The estimated regression equation for a model involving two independent variables and 10 observations is as follows:
\[ \hat{y} = 29.1270 + 0.5906x_1 + 0.4980x_2 \]
#### a. Interpret \( b_1 \) and \( b_2 \) in this estimated regression equation.
- **\( b_1 \)** represents the change in the dependent variable \( \hat{y} \) for a one-unit change in the independent variable \( x_1 \), keeping \( x_2 \) constant.
- **\( b_2 \)** represents the change in the dependent variable \( \hat{y} \) for a one-unit change in the independent variable \( x_2 \), keeping \( x_1 \) constant.
#### b. Predict \( y \) when \( x_1 = 180 \) and \( x_2 = 310 \) (to 2 decimals).
*The box is provided to input your calculated prediction based on the given values for \( x_1 \) and \( x_2 \).*
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