MATLAB: An Introduction with Applications
MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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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 \( x_2 \).*
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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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