WU QA 252 Multiple Regression Model to Predict Fair Market Value Questions

WU QA 252 Multiple Regression Model to Predict Fair Market Value Questions ORDER NOW FOR CUSTOMIZED AND ORIGINAL ESSAY PAPERS ON WU QA 252 Multiple Regression Model to Predict Fair Market Value Questions I’m working on a statistics question and need guidance to help me understand better. Hello, we need to answer the questions in the Doc file from the Excel database sheet, additional information included in the Word file. attachment_1 attachment_2 WIDENER UNIVERSITY SCHOOL OF BUSINESS ADMINISTRATION QA252 – Regression Project Thorpe 100 Points Fall 2020 Nassau County is located approximately 25 miles east of New York City. Data in the file GLENCOVE20FA (available in the Week Module files) are from a sample of 30 single-family homes located in Glen Cove. Variables included are the fair market value (in thousands of dollars), land area of the property (acres), interior size of the house (square feet), and age (years). Provide your answers to the questions below within this document. Additional Excel output can also be copied and pasted into the document. Upload your completed WORD document using the assignment link within the Weekly Module. (1) Construct a correlation matrix of all variables. (10) Which variable has the strongest linear relationship with fair market value of a home? What is the correlation value? (2) Develop a multiple regression model to predict fair market value of a home using all of the independent variables. (15) State the multiple regression equation. (15) Interpret the meaning of all the slopes of the equation (be sure to use appropriate units of measure). (10) Interpret and explain the meaning of the adjusted r2. (5) If you wanted to improve the adjusted r2, suggest an additional independent variable that you might want to add to the model to help predict the fair market value of a home. (10) Interpret and explain the meaning of the Standard Error. (10) At the .05 level of significance, determine whether each independent variable makes a significant contribution to the regression model. On the basis of these results, are all of the independent variables significant in the model? (10) Predict the fair market value for a house that has a land area of .25 acres, with an interior size of 2200 square feet, and is 30 years old. (15) Perform a residual analysis on your results. Are the regression assumptions valid for these data? Address Fair Market Value ($000) Property Size (acres) Age House Size (square feet) 9 Sycamore Road 522.9 0.2297 56 2448 21 Jefferson St 425.0 0.2192 61 1942 38 Hitching Post Lane 539.2 0.1630 39 2073 4 Poppy Lane 628.2 0.4608 28 2707 5 Daniel Drive 490.4 0.2549 56 2042 15 Francis Terrace 487.7 0.2290 98 2089 23 Guilfoy Street 370.3 0.1808 58 1433 17 Carlyle Drive 777.9 0.5015 17 2991 8 Craft Avenue 347.1 0.2229 62 1008 22 Beechwood Ct. 756.8 0.1300 25 3202 14 Fox Street 389.0 0.1763 64 2230 1 Raynham Road 889.0 1.3100 62 1848 2 Jerome Drive 452.2 0.2520 56 2100 7 Valentine Street 412.4 0.1148 22 1846 38 Jefferson Street 338.3 0.1693 74 1331 15 Inwood Road 334.3 0.1714 62 1344 29 Meadowfield Lane 437.4 0.3849 54 1822 13 Westland Drive 644.0 0.6545 56 2479 79 Valentine Street 387.8 0.1722 62 1605 13 Fairmont Place 399.8 0.1435 88 2080 1 Prestwick Terrace 356.4 0.2755 81 2410 11 Clement Street 346.9 0.1148 107 1753 7 Woodland Road 541.8 0.3636 55 1884 36 Elm Avenue 388.0 0.1474 51 2050 17 Duke Place 564.0 0.2281 50 2978 12 Prospect Avenue 454.4 0.4626 92 2132 1 Buckeye Road 417.3 0.1889 64 1551 30 Ann Street 318.8 0.1228 54 1129 26 Broadfield Place 519.8 0.1492 44 1674 16 Jackson Street 310.2 0.0852 104 1184 Get a 10 % discount on an order above $ 100 Use the following coupon code : NURSING10