Professor
a Statistics Professor Investigated Some of the Factors That $$y = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 3 } + \epsilon$$

Professor
A statistics professor investigated some of the factors that affect an individual student's final grade in his course.He proposed the multiple regression model $$y = \beta _ { 0 } + \beta _ { 1 } x _ { 1 } + \beta _ { 2 } x _ { 2 } + \beta _ { 3 } x _ { 3 } + \epsilon$$ where:
y = final mark (out of 100)
x₁ = number of lectures skipped
x₂ = number of late assignments
x₃ = mid-term test mark (out of 100)
The professor recorded the data for 50 randomly selected students.The computer output is shown below. The regression equation is:
$$\hat { y } = 41.6 - 3.18 x _ { 1 } - 1.17 x _ { 2 } + .63 x _ { 3 }$$
$\begin{array}{l|lll|}\hline \text { Predictor } & \text { Coef } & \text { StDev } & T \\\hline \text { Constant } & 41.6 & 17.8 & 2.337 \\x_{1} & -3.18 & 1.66 & -1.916 \\x_{2} & -1.17 & 1.13 & -1.035 \\x_{3} & 0.63 & 0.13 & 4.846 \\\hline\end{array}$
$$S = 13.74$$
$$\mathrm { R } - \mathrm { Sq } = 30.0 \%$$
Analysis of Variance
$\begin{array}{l|llll}\hline \text { Source of Variation } & \text { df } & \text { SS } & M S & F \\\hline \text { Regression } & 3 & 3716 & 1238.667 & 6.558 \\\text { Error } & 46 & 8688 & 188.870 & \\\hline \text { Total } & 49 & 12404 & & \\\hline\end{array}$
-Do these data provide enough evidence to conclude at the 5% significance level that the final mark and the number of skipped lectures are linearly related?
Test statistic = ____________________
Critical Value = ____________________
Conclusion: ____________________