Cellular.txt Tab delimited.
Cellular.jmp
Question 1. Task: transformation and exploration in the cellular dataset.
Obtain the cellular dataset.
Cellular.txt Tab delimited.
Cellular.jmp
This dataset contains data on the number of cellular phone subscribers in the United States on a six-monthly basis from 1984 until 1995.
1a. Explore a variety of transformations of the subscribers variable. Suggest a ``best transformation'' to linearity. Justify your choice. Based on your choice of transformation, extrapolate in whatever way you like to estimate subscribers for 1996 in months 6 and 12, and 1997 in months 6 and 12.
1b. Examine the suggestion that the pattern of growth has changed over the 11 year period. In particular compare the pattern of growth up until Dec. 1989 to the subsequent growth pattern. Comment on any similarities or differences.
Question 2. Task: investigate the impact on housing prices of a ``pollution event''.
Obtain the pollute dataset.
Pollute.txt Tab delimited.
This dataset is an extract from that used in the paper
Mendelson,R., Hellerstein,D., Huguenin,M., Unsworth,R. and Brazee,R. Measuring Hazardous Waste Damages with Panel Models. Journal of Environmental Economics and Management 22, 259-271. (1992)
The data used come from single family home sales in the harbor area surrounding New Bedford, MA. PCB's were/are allegedly present in New Bedford harbor. Though their presence was first revealed in 1976, for the purpose of this analysis assume that the pollution event occurred on January 1 1982.
All house prices are given in constant 1989 dollars.
This dataset contains houses that had a sale prior to 1982 and also after 1982. Prices of the sales are in the variables named post82price and pre82price. It also contains the number of years between the two sale dates in the variable years. The variable renovate is the amount spent on renovations between the two sales. Finally the variable area is a categorical variable taking on the value 1 for those houses in the polluted area and 0 for those outside the area.
Objective: through exploratory data analysis, transformation and visualization comment and if possible estimate the impact of the pollution event on house prices. Explicitly state any assumptions in your analysis and if relevant describe additional information that might help in refining the analysis.