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Statistical Project - Home Sales The project examined the descriptive statistics of a sample of home sales in the geographical area including northern Columbus,
a statistical program called SPSS. These results can be found in Appendix A. On the basis of these results, recommendations are given to Caddyhome regarding these
and eating out. Besides, they also note that there is no significant statistical correlation between unemployment and DIY sales. 2.1.2c Level of owner occupation
authors were able to strengthen the conclusions to include a more cohesive model of the home sales market. Another step taken to gain more from the hypothesis was
retail format in which the retailer and customer communicate which each other through an interactive electronic network. After an electronic dialogue between the
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The project examined the descriptive statistics of a sample of home sales in the geographical area including northern Columbus, Westerville and Gahanna. The sample data of 67 homes was provided via a link in the MATH 215 Assignment 1-2, Project I (Franklin University, 2006). The elements of interest were the selling prices, number of bedrooms, as well as other elements selected by the student. Basic statistical terminology was used throughout the project. Included in this document are measures of central tendency, computation and interpretative measures of dispersion/variability, analysis of a data set with outliers, and charts and graphs to assist with the interpretation of the data. Additionally Chebyshev’s rule and the Empirical rule as defined in the Essentials of Modern Business Statistics with Microsoft® Excel, 3e (Anderson, Sweeney, & Williams, 2007, p. 116) were analyzed and discussed. The descriptive statistics techniques were also applied to a business situation.
Methods
The sample data was collected from the MATH 215 Assignment 1-2, Project 1 (Franklin University, 2006) link and was used without modifications, additions or deletions.
Using Microsoft® Excel 2003, the raw data regarding the home selling price elements were used to determine the mean, medium, mode, standard deviation, and quartiles. In addition, a calculation of the third quartile minus the first quartile produced the interquartile range. The lower and upper limits from the quartiles, which are one and one-half of the quartile range, were also calculated (see Appendix for Table 1.1).
The mean and the standard deviation were used to calculate the number and percentage of homes that were one, two, and three standard deviations from the mean (see Appendix for Table 1.2). The information in Tables 1.1 and 1.2 were used to create a box plot (see Chart 1.2). Using a class width of $25,000, the frequency distribution of home selling prices was calculated (see...
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