The Computer Output for the Multiple Regression Model $y = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \varepsilon$

question 79

Essay

The computer output for the multiple regression model $y = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \varepsilon$ is shown below. However, because of a printer malfunction some of the results are not shown. These are indicated by the boldface letters a to i. Fill in the missing results (up to three decimal places). $$\begin{array} { | c | c c c | } \hline \text { Predictor } & \text { Coef } & \text { StDev } & \text { T } \\\hline \text { Constant } & \boldsymbol { a } & 0.120 & 3.18 \\x _ { 1 } & 0.068 & \boldsymbol { b } & 3.38 \\x _ { 2 } & 0.024 & 0.010 & \boldsymbol { c } \\\hline\end{array}$$ S = d R-Sq = e. $$\begin{array}{l}\text { ANALYSIS OF VARIANCE }\\\begin{array} { | l | c c c c | } \hline \text { Source of Variation } & \mathrm { df } & \mathrm { SS } & \mathrm { MS } & \mathrm { F } \\\hline \text { Regression } & 2 & 7.382 & \boldsymbol { g } & \boldsymbol { i } \\\text { Error } & 22 & f & h & \\\hline \text { Total } & 24 & 7.530 & & \\\hline\end{array}\end{array}$$

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Definitions:

Coefficient

In mathematics and statistics, a coefficient is a multiplicative factor in some term of a polynomial, series, or expression; it is usually a number, but in any case does not involve any variables of the series.

Linearly Related

Refers to a correlation between two variables in which a variation in one is linked to a corresponding change in the other.

Interaction Term

In statistical models, a variable created by multiplying two or more variables together to investigate if the effect of one variable on the dependent variable is different at different levels of the other variable.

Coefficient

A numerical constant placed at the beginning and serving as a multiplier to a variable in an algebraic formula.