Business Statistics Assignment

The EXCEL assignment uses housing data developed by Professor Robert Shiller of Yale University and his associates.  The data can be found at–p-us—-

Select these three cities that have had very different housing markets: San Francisco, Seattle and Portland.  Use data from January 2000 till the latest available month. For each question calculate the answer using EXCEL and then write an explanation of your conclusion.  Include both the results and explanation in your write-up.  Make sure you highlight all the important numbers in the EXCEL outputs and state what they are.

Before analyzing any data, you have to have to research the background of the data.  First, what is S&P Case Shiller Index?  Compare this index to Realtor data available on the web or obtained by speaking to a realtor.   Are there any problems or biases in data published by the housing industry or by realtors (e.g., National Association of Realtors NAR)?  What is the method by which data are collected for Case Shiller Index?  What does a 100 in the Index mean?  If it the Index is at 125, what does it mean for home prices at that point in time?
What does seasonality or seasonal adjustment mean?  What changes can you expect to see in monthly pricing data when the prices are “seasonally adjusted” as compared to no adjustment (which is just data as collected)?
What general overall conclusions can you come up with regarding home prices in the three cities?  You need not make statistical statements for question 1 but general managerial comments would be suitable.  Research some trends that were going on in the US, be it in government, economy or society, and try to explain if any of these might have influenced prices.
Calculate the mean of the index in each city across all the months in the data (from January 2000 onwards only).  What does it mean?
Plot the prices for Seattle over time.  When would you say the prices peaked?  Would you say that home prices have reached bottom and are recovering now?  Would you make the same conclusion for San Francisco and Portland?
Many homeowners are underwater on their mortgages and home values.  What does the term mean?  How long ago would you have had to buy your home in the Portland market so that your home is worth at least as much as you paid for it?  Are homeowners more likely to be underwater in Seattle or San Francisco?  If some people bought a home in the Seattle area in January 2000, would you say they made a wise investment as compared to leaving their money in a bank or stock market?
Calculate the standard deviations for the three cities and explain why they are different and how they are different.
What is the range of the index in Portland?  Discuss the movement of prices in Portland and show why range is a more accurate measure rather than looking at the starting and ending points of prices in this time range.
Construct a histogram of the prices in San Francisco using class intervals. Interpret the Histogram.  Make sure you choose appropriate class intervals, so that the Histogram is easy to interpret.
How would you create a pie-chart to analyze the data? Are there any other graphical techniques that you could use here?  Note: For questions 9 and 10 you will get poor charts if you just input the columns of data in the EXCEL into the charts as there are too many categories.  You need to create fewer categories first.
Are the price patterns over time different in Seattle as compared to Portland?  What factors could explain this pattern? Provide some explanation from your understanding of national economics and statistics (you could try Wall Street Journal,, or even Google).
What is the correlation coefficient of prices between each pair of cities?  Provide a business explanation why some of the correlations may be high (or low).
Are the mean prices of Seattle significantly different statistically from the mean prices of New York City (you have to do a statistical test to answer this question)?  Make some comments on what the index means.  Use EXCEL and your textbook to understand statistical significance. Note: Statistical significance requires a formula and cannot be determined visually!  What does statistical significance mean in this situation?
Think about one or more variables that you believe might affect house prices.  Could you find monthly data for these variables?  Use the house price index as the dependent variable and these new variables as independent variables and run a regression for each city. (You get some extra credit if you can find the economic, business and statistics variables with monthly data on the web or in the library – if you use number of months as the independent variable you will get partial credit)
Write a short article for a local publication and explain the real estate data and trends.  Examples:  Campus newspaper, Business Journal, opinion piece in Columbian, your home-town paper, etc.  You can identify yourselves as sophomore business students and the article was the result of a Project in your Business Statistics class.


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