Assignment: Case Study--Business Operations, Forecasting: Real Estate Industry

You are the marketing manager for Acme Realty, a real estate company specializing in listings in upscale Hillsborough, California. You have been asked to forecast sales for the coming year.

You have two sets of data at your disposalHome Sales History and Home Sales Detail.

1. Home Sales History: The history data set shows the average home sales price for every quarter from January 2008 through August 2010. Table 1 below shows the data.
2. Home Sales Detail: The detail data set shows details of recent home sales, including the sales price, the house size in square feet, and the lot size in square feet. Table 2 shows the data.

To be thorough, you plan to build two models. The first will use time series regression to forecast future sales, based on historic sales. The second will use causal regression to forecast sales prices based on the house size and lot size. Use these tables to answer the questions on the assignment page linked below.

Questions:

1. Answer the questions below by developing a time series forecast with the Home Sales History data set.

a. What is the Y-intercept value?

b. What is the X (time, or date) coefficient?

c. What is the defining equation relating Price and Time?

d. What would be the forecasted sales for 2011?

2. Answer the questions below by developing a causal analysis forecast with the Home Sales Detail data set. Forecast the price for a house size of 4000 sq. ft. and a lot size of 22000 sq. ft. Use causal regression.

a. What is the Y-intercept value?

b. What is the X1 (House Size) coefficient?

c. What is the X2 (Lot Size) coefficient?

d. What is the defining equation relating Price, House Size, and Lot Size?

e. What would be the forecasted price for a house size of 4000 sq. ft. and a lot size of 22000 sq. ft.?

3. Record your observations about the forecasting process. How accurate is it? How could you improve it?

Table 2: Home Sales Detail \begin{tabular}{|c|c|c|c|} \hline House & Price (\$M) & House (K sf) & Lot (K sf) \\ \hline House 1 & 6.0 & 6.9 & 42.7 \\ \hline House 2 & 5.8 & 8.0 & 36.6 \\ \hline House 3 & 5.6 & 8.0 & 44.0 \\ \hline House 4 & 3.5 & 3.8 & 18.0 \\ \hline House 5 & 3.4 & 6.1 & 27.4 \\ \hline House 6 & 3.4 & 4.3 & 22.2 \\ \hline House 7 & 2.7 & 3.8 & 22.0 \\ \hline House 8 & 2.6 & 5.0 & 29.3 \\ \hline House 9 & 2.6 & 3.6 & 31.4 \\ \hline House 10 & 2.3 & 3.1 & 22.2 \\ \hline House 11 & 2.3 & 3.9 & 21.7 \\ \hline House 12 & 2.3 & 3.2 & 24.4 \\ \hline House 13 & 1.9 & 3.5 & 25.3 \\ \hline House 14 & 1.9 & 3.4 & 24.0 \\ \hline House 15 & 1.9 & 3.2 & 21.8 \\ \hline House 16 & 1.6 & 3.3 & 6.6 \\ \hline House 17 & 1.6 & 2.3 & 15.9 \\ \hline House 18 & 1.5 & 2.3 & 21.2 \\ \hline \end{tabular}