In Part 1, descriptive statistical methods are used to examine the distributions of each variable used in a study of a local real estate market. Appropriate visuals may be used and i

In Part 1, descriptive statistical methods are used to examine the distributions of each variable used in a study of a local real estate market. Appropriate visuals may be used and included in the case report. Distributions are checked for outliers using z-scores. Outliers should always be noted by their actual value and z-score. For categorical data like age category and home type, the frequency distributions are reported. Any categories with very low frequencies should be noted. Appropriate visuals may be used. Relationships between home characteristics and home prices are also analyzed in Part 1, using descriptive statistical methods: Categorical home characteristics, age category, and type are used to group home prices. Report on the distributions of home prices by home characteristic category. In particular, consider any mean difference that would indicate a strong effect. All summary statistics should be reported and the data should be screened for any outliers. Categorical home characteristics may be used in cross-tabulation with the home prices in categories. The frequency distributions of the price category by home characteristic category should be examined and reported. Notable differences should be highlighted because they may indicate a particularly strong effect. Quantitative characteristics also have effects on price. Simple linear regression is used to examine the relationship between two quantitative variables. Report on the form, direction, and strength of the linear relationships, if any. Each simple linear regression should also be checked for regression outliers. Finally, the regression equations and effect sizes are also reported. After completing the specified analysis results may include: A profile of a typical home in this market, noting anything unusual or possibly problematic in the sample data (such as outliers or very different standard deviations among groups) A clear description of the observed effects of home characteristics on price. Which characteristic seems to have the strongest effect? Weakest? What specific results of the analysis give evidence to support your overall findings. Our results will grow as we conduct further analysis. Part 2 In Part 1 you described the categorical home characteristics and linear relationships between the quantitative characteristics of a home and the price. In this section of the case, you will build on the linear regression models you created by leveraging multiple regression. What is the best possible regression model that may be used to forecast home price with home characteristics? Using the stepwise multiple regression method, determine the independent variables that should be used. Conduct appropriate residual analysis to check model assumptions and regression outliers. Remove any outliers you determine should be removed. Be sure to explain why any data are removed. Key findings may include (but do not need to be limited to): In terms of the home preferences described in Part 2, how much should you expect to pay for such a home in this market? Report on the cost/benefit analysis of home characteristics: What are some characteristics that affect home prices? What other factors not considered by your regression model do you think would further explain home prices? Using your forecast intervals of home price and consideration of other factors affecting price, what should be considered if you want to purchase a home toward the low or high end of the interval range? For this multiple regression analysis, not all home characteristics could be used together. What home characteristics were rejected? Would these discarded variables be helpful to use in addition to the model you determined with the stepwise method? Why/why not? The Final Report should be a formal report that contains the following sections: Abstract – A brief summary of your work in everyday language Background – A brief summary of the analysis Objectives – What questions are you trying to answer? Summary Statistics and Summary Figures (This should be the work in Case Study Part 1) Methods/Analysis (This should be the work in Case Study Part 1 and 2) Results and Conclusions/Discussion (This should be the work in Case Study Part 1 and 2) References (Works Cited) Appendix/Supplemental Information (Specific Information/Data you used for your report) Defining unique terms you use in your analysis (required) If you used code to generate Figures and Tables (optional) Data used and how you manipulated the raw data (optional) Models used in analysis, including model assumption checks (required)