Case Study #4 will assess your ability to apply the concepts of chapter 10 to conduct simple and multiple regression analyses to create a prediction model for home prices based on up to four independent variables. You will calculate various descriptive statistics, create summary tables, create various charts and develop five regression prediction models. Finally, you will create a written report summarizing your findings. You will need to use the Data Analysis ToolPak Add-in as you did for the previous two case studies.
The data file contains data for a random sample of 1,000 houses located in the greater Baltimore, MD area. The data fields included are as follows:
In developing both your model and the report, address the items below.
c. A section (1 or more paragraphs) describing how the frequency histograms from step 3 support and clarify the findings of the tabular data. Include in this section any evidence suggesting outliers in the data.
Submit a single Excel workbook showing all work for Steps 2-7 and a Word document of your summary report that addresses all parts of Step 8 and that also includes/interweaves all supporting tables and charts from Steps 2-7 (to tell a story with the data and through visualization means).
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