Refer to the Real estate sales data set in Appendix C. 7 and Case Study 19.59. Carry out a balanced two-way analysis of covariance of this data set where the response of interest is sales price (variable 2), the two crossed factors are quality (variable 10) and style (variable II), and the possible covariates are finished square feet (variable 3) and lot size (variable 12). Style is recoded as either I or not I. Order the observations in the six factor-level-combination cells from smallest to largest observation number and retain the first 25 observations in each cell for a total of 150 observations. The analysis should consider transf0I1l1ations of the response variable and the covariates, Document the steps taken in your analysis and justify your conclusion~,
Case Study 19.59
Refer to the Real estate sales data set in Appendix C. 7. Carry out a balanced two-way analysis of variance of this data set where the response of interest is sales price (variable 2) and the two crossed factors are quality (variable 10) and style (variable II). Style is recoded as either 1 or not 1. Order the observations in the six factor-level-combination ceIls from smallest to largest conservation number and retain the first 25 observations in each cell for a total of 150 observations. The analysis should consider transformations of the response variable. Document the steps taken in your analysis and justify your conclusions.
Appendix C.7
The city tax assessor was interested in predicting residential home sales prices in a Midwestern city as a function of various characteristics of the home and surrounding property. Data on 522 arms-length transactions were obtained for home sales during the year 2002. Each line of the data set has an identification number and provides information on 12 other variables. The 13 variables are:
