In Chapters 4 and 13 we considered what factors might contribute to the price of a home. In Chapter 4 we looked at living area and in Chapter 13 we considered such features as whether the home had a fireplace or more than 2 bedrooms. In those initial analyses, we used correlation and regression and Student’s t- based methods. However, a careful look at the data reveals that the assumptions required by those methods are dubious. The data file is Real Estate. Return to those questions, this time using appropriate nonparametric methods. Specifically, consider:

Does the price for homes with a fireplace differ significantly from the price for homes without fireplaces? Make an appropriate display and discuss whether a nonparametric method is preferable to a t- test. Select an appropriate non-parametric test and compare the results.

Does the price for homes depend on the number of bedrooms? Code the bedrooms as 1, 2, 3, or 4 or more. Make an appropriate display and discuss whether nonparametric methods are preferable to an ANOVA for comparing central values of these groups. Perform an appropriate nonparametric test and report on your findings.

Does the price of a home depend on its living area? Make a scatterplot and ­discuss whether a nonparametric method would be more appropriate than Pearson correlation for discussing this question. Select an appropriate method, and discuss your conclusions.