Reference no: EM133015416
1. Compute the outlier indicators for the PRICE by STYLE data. Note:
use the inclusive, not exclusive quartile for this.
a. Investigate if there are possible outliers in any of the PRICE by STYLE data. If so, which styles and what values and why?
b. Discuss the implications for the interpretations of the summary measures, histograms, and boxplot and using them for coming to conclusions on how prices differ by style.
2.attach a Crosstab table and corresponding side-by-side bar chart and 100% stacked column chart for the variables STYLE and VIEW by creating a pivot table. Consider selecting a home in the data set at random (uniformly). Explain how you would compute the following statistics and interpret the results. Always provide the specific statistics in your answer e.g. if discussing the most frequent thing, state what the frequency is and any comparison frequencies if needed.
a. Most likely a house will have what quality of view?
b. How likely will it not have this (the most frequent) quality of view? Why is this different than the least frequent quality of view?
c. What is the most likely quality of view and style?
d. How likely will a home have that quality of view or be that style?
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Compute the outlier indicators for the price by style
: 1. Compute the outlier indicators for the PRICE by STYLE data. Note: use the inclusive, not exclusive quartile for this.
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