Assignment Question

North Valley Real Estate Case Study – Part 2

The purpose of this assignment is to conduct inferential statistical analysis and interpret the results. Recall in Part 1 of the case study you performed descriiptive analysis for the project referring to the historical data for the market/selling price of the homes. For Part 2 of the case study project, you will leverage inferential statistics to estimate the market price, or future selling price, of the homes. The variable name will remain Price. Reference the “SYM-506 North Valley Real Estate Case Study Variables” resource.Utilize the statistical analysis methods and concepts you have learned thus far in the course to address the following questions in an Excel spreadsheet. Additionally summarize your findings from each exercise in a brief summary. This assignment will be integrated into the final paper for the case study project in Topic 8, which will require APA formatting for the tables, charts, and graphs developed in this Part 2 assignment

Exercise 1: Correlation and Linear Regression

For the following exercise, characterize the relationship of the variables and interpret the F-test for the regression model. Using the p-value approach, determine whether the null hypothesis for the F-test is rejected or not. Discuss why or why not. Interpret the implication of these findings for the model. (a) Can you determine any correlation between the independent variables Days (number of days the property is on the market) and the Price (market price in dollars)? Similarly, are the Size (livable square feet of the property) and the Price (market price in dollars) correlated? Use the .05 significance level. State the p-value of the test. (b) With the Price (market price in dollars) as the dependent variable and the Size (livable square feet of the property) of the home as the independent variable, determine the regression equation and interpret the confidence level, the precision, and reliability of the sample. Using the regression model, forecast the future market Price for a home with a livable area of 2,200 square feet. Determine the 95% prediction interval for the market price of a home with a livable area of 2,200 square feet.

Exercise 2: Multiple Regression Analysis

Conduct the following analyses using the Price (market price in dollars) as the dependent variable, determine the regression equation with the Bedrooms (number of bedrooms), Size (livable square feet of the property), Township (area the property is located), and the Baths (number of bathrooms) as independent variables. (a) Develop a correlation matrix and discuss which independent variables have strong or weak correlations with the dependent variable. Utilize these results to discuss any issues with problems with the multicollinearity. (b) Use Excel to determine the multiple regression equation. Discuss how you selected the variables to include in the equation. Your regression equation should demonstrate a significant relationship. Report and interpret the R-square. (c) Using your results from Question (b) evaluate the addition of the variables; Pool (1 = yes, 0 = no), and attached Garage (1 = yes, 0 = no). Report your results and conclusions. (d) Develop a histogram of the residuals from the final regression equation developed in Question (c). Is it reasonable to conclude that the normality assumption has been met? (e) Plot the residuals against the fitted values from the final regression equation developed in Question (c). Plot the residuals on the vertical axis and the fitted values on the horizontal axis. General Requirements Submit both the Excel spreadsheet showcasing the statistical analysis and the summaries in the Word document. APA style is not required.