Students a Growing School District Tracks the Student Population Growth $\begin{array}{l}\text { students }=119.53+172.03 \text { year } \\ \text { Sample size: } 6 \\ \text { R-sq }=0.987\end{array}$

Students A growing school district tracks the student population growth over the years from 2008 to 2013. Here are the regression results and a residual plot.
$\begin{array}{l}\text { students }=119.53+172.03 \text { year } \\ \text { Sample size: } 6 \\ \text { R-sq }=0.987\end{array}$



a. Explain why despite a high R-sq, this regression is not a successful model.
To linearize the data, the log (base 10) was taken of the student population. Here are the
results. Dependent Variable: $\log$ (students)
Sample size: 6
$R-s q=0.994$

$\begin{array}{lrr}\text { Parameter } & \text { Estimate } & \text { Std. Err. } \\ \text { constant } & 2.871 & 0.0162 \\ \text { year } & 0.0389 & 0.00152\end{array}$



b. Describe the success of the linearization.
c. Interpret R-sq in the context of this problem. d. Predict the student population in 2014.

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a. Even though R-sq = 98.7%, the residua...

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