1. A little peek at the Autorama Consider the 80.5 expected car buyer in the $45,000–$55,000 income group from the Autorama case. Using the same assumptions we made for the case, determine the expected number of sales in each price bracket from this group. Hint: Use the normal distribution to determine the probability that someone in this group would buy a car in each price bracket. You may wish to do your calculations in a spreadsheet. 2. Shore Realty Shore Realty sells real estate in Oklahoma. The company would like to be able to predict the selling price of new homes based on the home’s size. It has collected data on size (“sqfoot” in square feet) and selling price (“price” in dollars), which are stored in the ﬁle shore.xls. Use the data in that ﬁle to answer the following questions: • Use Kstat or Excel to construct a scatterplot for these data with size on the horizontal axis. • Use Kstat to dtermine the estimated regression equation. • Predict the selling price for a home with 2,600 square feet. 3. Accesss bschools2002.xls which contains data regarding the top 30 business schools based on the 2002 Business Week ratings. Many business schools surveys including this one report mean base salaries and median base salaries. These two statistics tend to be similar. KStat can help us ﬁnd a relationship between the two for this dataset. (a) Use KStat to construct a scatterplot with mean base salary on the vertical axis and median base salary on the horizontal axis. (b) Does the relationship appear linear? (c) Use KStat to perform a regression of mean base salary vs. median base salary. Write out the estimated regression line. (d) Use your regression equation to estimate themean base slary for a school with a median base salary of $77,000. (e) Use your regression equation to estimate the mean base salary for a school with a median base salary of $88,000.
4. Accesss bschools2002.xls which contains data regarding the top 30 business schools...
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