Government is looking to upgrade the local public transport system and wishes to develop a model to predict time spent to commute on public transport, measured in minutes, based on age. The Excel data below, contains these data for 100 respondents. Use Excel Data Analysis to estimate a linear model for the relationship, as well as the 99% confidence interval for the slope coefficient and the residual plot. State all numeric answers below correct to 4 decimal places using the Excel output results.

1. the intercept ,

2. the slope coefficient , and

3. the standard error of the estimate.

4. Using this model, predict the time spent on public transport for person that is 45 years old. Use all decimal places in your calculation by selecting and using the values of b0 and b1 in the output generated by Excel.

5. Does the prediction involve extrapolating the relationship? Type yes or no. State the 6. lower bound and 7. upper bound for the 99% confidence interval for the slope coefficient

Data:

\begin{tabular}{|r|r|} \hline 29 & 81.09 \\ \hline 37 & 30.528 \\ \hline 16 & 14.31 \\ \hline 32 & 47.7 \\ \hline 59 & 68.688 \\ \hline 34 & 17.172 \\ \hline 58 & 53.424 \\ \hline 38 & 32.436 \\ \hline 16 & 67.734 \\ \hline 12 & 18.126 \\ \hline 23 & 87.768 \\ \hline 23 & 44.838 \\ \hline 24 & 52.47 \\ \hline 27 & 82.998 \\ \hline 24 & 11.448 \\ \hline 50 & 49.608 \\ \hline 29 & 34.344 \\ \hline 41 & 37.206 \\ \hline \end{tabular} \begin{tabular}{|r|r|} \hline 29 & 81.09 \\ \hline 37 & 30.528 \\ \hline 16 & 14.31 \\ \hline 32 & 47.7 \\ \hline 59 & 68.688 \\ \hline 34 & 17.172 \\ \hline 58 & 53.424 \\ \hline 38 & 32.436 \\ \hline 16 & 67.734 \\ \hline 12 & 18.126 \\ \hline 23 & 87.768 \\ \hline 23 & 44.838 \\ \hline 24 & 52.47 \\ \hline 27 & 82.998 \\ \hline 24 & 11.448 \\ \hline 50 & 49.608 \\ \hline 29 & 34.344 \\ \hline 41 & 37.206 \\ \hline \end{tabular}