Silver Screen Inc. is a movie distribution company. It has kept records of total annual movie ticket sales for one community over ten years. These data have been related to other publicly available data as shown in Table 3.8.
For these data:
(a) Plot the data so that you can advise Silver Screen's management on a predictive model for movie ticket sales for the next few years.
(b) Discuss the relative merits of various regression and smoothing models with reference to the available data.
(c) Calculate both simple and multiple regressions.
$$
\begin{array}{llll}
\hline \hline \text { Year } & \text { Ticket sales } & \text { Households } & \begin{array}{l}
\text { Average household } \\
\text { income (\$/year) }
\end{array} \\
\hline 1992 & 75,000 & 20,000 & 32,250 \\
1993 & 82,000 & 20,850 & 34,825 \\
1994 & 81,100 & 22,000 & 37,580 \\
1995 & 85,250 & 21,800 & 42,015 \\
1996 & 94,350 & 21,450 & 41,870 \\
1997 & 92,700 & 22,100 & 44,280 \\
1998 & 95,280 & 23,750 & 47,850 \\
1999 & 96,480 & 24,100 & 49,250 \\
2000 & 94,300 & 24,800 & 51,380 \\
2001 & 97,800 & 25,370 & 54,890 \\
\hline \hline
\end{array}
$$
(d) Calculate moving average, weighted moving average and exponential smoothing models.
(e) Establish three-year forecasts under each of the above models.
(f) Advise management as to the suitability and reliability of forecasts established under each model.