## Related questions with answers

Oakland passengers 2016 Part $\mathrm{I}$ of this exercise is pretty much as it appeared in the previous edition of this textbook:

The scatterplot below shows the number of passengers departing from Oakland (CA) airport month by month since the start of 1997. Time is shown as years since 1990, with fractional years used to represent each month. (Thus, June 1997 is $7.5$-halfway through the 7 th year after 1990.)

Dependent variable is Passengers

$\begin{array}{lc}\text { R-squared }=71.1 \% & \mathrm{~s}=104330 \\ \text { Variable } & \text { Coefficient } \\ \text { Constant } & 282584 \\ \text { Year-1990 } & 59704.4\end{array}$

a) Interpret the slope and intercept of the model.

b) What does the value of $R^2$ say about the model?

c) Interpret $s_e$ in this context.

d) Would you use this model to predict the numbers of passengers in 2010 (YearsSince $1990=20$ ) Explain.

e) There's a point near the middle of this time span with a large negative residual. Can you explain this outlier?

Part II We updated the data through 2016 for this edition, and here is the scatterplot for data through 2016:

f) If you had used the model for the data through 2006 to predict the number of passengers in 2010 , how well would it have worked? Why?

g) Explain how this shows the danger of extrapolating. What are possible reasons for the sudden decline in airline travel in about 2008 ?

Solution

Verified### (a.)

Since $1990$, the number of passengers using the Oakland airport has increased to around $59,700$ per year, up from around $282,000$ in $1990$.

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