The analysis ofhouse pricesin Springfield that was conducted . show multiple regression model for Price

1. Using R determine the multiple regression equation for Price using the quantitative as well as qualitative (categorical) variables in the data set. Create dummy variables for the categorical variables and use "North" as the base (or reference) category for the Neighborhood variable, and "No Brick" as the base category for exterior construction material variable, Brick. Call this modelModel 1. Copy and paste the command and output generated by R.
2. State the multiple regression equation forModel 1.
3. Interpret the meaning of the coefficients inModel 1within the context of the problem.
4. Determine and interpret the coefficient of determination,r2, forModel 1.
5. Conduct a hypothesis test to determine the overall fit ofModel 1. Use 0.05 level of significance.
6. State the null and alternative hypotheses.
7. Report the test statistic.
8. Report the p-value.
9. Determine the statistical conclusion and communicate the results of the test within the context of the problem.
10. Comment on the significance of each of the predictors inModel 1. Use 0.05 level of significance.
11. UsingModel 1estimate the price of a 1620 sq ft. brick house in the North that has 3 bedrooms, 2 bathrooms and has had 1 offer made on it.
12. EnhanceModel 1with interaction term for "Brick" and the neighborhoods. Call this modelModel 2.Copy and paste the command and output generated by R. State the multiple regression equation forModel 2.
13. UsingModel 2estimate the price of a 1620 sq ft. brick house in the North that has 3 bedrooms, 2 bathrooms and has had 1 offer made on it.
14. Compare the overall fit betweenModel 1andModel 2.What model would you recommend to predict Price? Explain.

You need to have JavaScript enabled in order to access this site. Dashboard BMSO600 Skip To Content Dashboard Account Dashboard Courses Groups Calendar Inbox CourseEval Help EMT Course Policies Logout Close Object 1 My Dashboard BMSO600 Assignments Week 12: Practice Problems Summer I 2020 Home Announcements Syllabus Assignments Grades People Quizzes Course Reserves WebEx Adobe Creative Cloud Week 12: Practice Problems Submit Assignment Due Aug 1 by 11:59pm Points 50 Submitting a file upload Be sure to read the instructions below before getting started. Instructions: Review the data file and answer the questions. Your answers should be submitted in the form of a Word document. The Word document should include any charts, tables, or graphs you create. You are also required to submit an Excel file, R code or copy of hand calculations to support your answers. Problem Description and Questions This week's practice problem and questions extends the analysis of house prices Minimize File Preview Object 2 in Springfield that was conducted in Week 1: Practice Problems. You will create a multiple regression model for Price. a. Using R determine the multiple regression equation for Price using the quantitative as well as qualitative (categorical) variables in the dataset. Create dummy variables for the categorical variables and use \"North\" as the base (or reference) category for the Neighborhood variable, and \"No Brick\" as the base category for exterior construction material variable, Brick. Call this model Model 1. Copy and paste the command and output generated by R. b. State the multiple regression equation for Model 1. c. Interpret the meaning of the coefficients in Model 1 within the context of the problem. d. Determine and interpret the coefficient of determination, r2, for Model 1. e. Conduct a hypothesis test to determine the overall fit of Model 1. Use 0.05 level of significance. 1. State the null and alternative hypotheses. 2. Report the test statistic. f. g. h. i. j. 3. Report the p-value. 4. Determine the statistical conclusion and communicate the results of the test within the context of the problem. Comment on the significance of each of the predictors in Model 1. Use 0.05 level of significance. Using Model 1 estimate the price of a 1620 sq ft. brick house in the North that has 3 bedrooms, 2 bathrooms and has had 1 offer made on it. Enhance Model 1 with interaction term for \"Brick\" and the neighborhoods. Call this model Model 2. Copy and paste the command and output generated by R. State the multiple regression equation for Model 2. Using Model 2 estimate the price of a 1620 sq ft. brick house in the North that has 3 bedrooms, 2 bathrooms and has had 1 offer made on it. Compare the overall fit between Model 1 and Model 2. What model would you recommend to predict Price? Explain. 1596340799 08/01/2020 11:59pm File Upload Google Doc BOX Upload a file, or choose a file you've already uploaded. File: remove empty attachment Add Another File remove empty attachment Click here to find a file you've already uploaded Cancel Submit Assignment Submitting... Select the file from the list below. Cancel Submit Assignment Retrieving a copy of your Google Doc to submit for this assignment. This may take a little while, depending on the size of the file... Rubric 826651 Can't change a rubric once you've started using it. Find a Rubric Title: Find Rubric Week 12 You've already rated students with this rubric. Any major changes could affect their assessment results. 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I'll write free-form comments when assessing students Remove points from rubric Don't post Outcomes results to Learning Mastery Gradebook Use this rubric for assignment grading Hide score total for assessment results Cancel Create Rubric pts / 5 pts -- pts / 5 pts -- How to use UMD Canvas Student Tutorial Faculty Tutorial Canvas Guides 9b69b057-6af1-45b9-bed4-08ebd74ecbb5 Keyboard Shortcutsclose ALT+F9 Open the editor's menubar ALT+F10 Open the editor's toolbar ESC Close menu or dialog, also gets you back to editor area TAB/Arrows Navigate left/right through menu/toolbar ALT+F8 Open this keyboard shortcuts dialog