| FloorArea (Sq.Ft.) | Offices | Entrances | Age | AssessedValue ($'000) |
| 4790 | 4 | 2 | 8 | 1796 |
| 4720 | 3 | 2 | 12 | 1544 | | The Excel file for this assignment contains a database with information about the tax assessment value assigned to medical office buildings in a city. The following is a list of the variables in the database: |
| 5940 | 4 | 2 | 2 | 2094 | | FloorArea: square feet of floor space |
| 5720 | 4 | 2 | 34 | 1968 | | Offices: number of offices in the building |
| 3660 | 3 | 2 | 38 | 1567 | | Entrances: number of customer entrances |
| 5000 | 4 | 2 | 31 | 1878 | | Age: age of the building (years) |
| 2990 | 2 | 1 | 19 | 949 | | AssessedValue: tax assessment value (thousands of dollars) |
| 2610 | 2 | 1 | 48 | 910 | | Use the data to construct a model that predicts the tax assessment value assigned to medical office buildings with specific characteristics. |
| 5650 | 4 | 2 | 42 | 1774 | | Construct a scatter plot in Excel with FloorArea as the independent variable and AssessmentValue as the dependent variable. Insert the bivariate linear regression equation and r^2 in your graph. Do you observe a linear relationship between the 2 variables? |
| 3570 | 2 | 1 | 4 | 1187 | | Use Excel’s Analysis ToolPak to conduct a regression analysis of FloorArea and AssessmentValue. Is FloorArea a significant predictor of AssessmentValue? |
| 2930 | 3 | 2 | 15 | 1113 | | Construct a scatter plot in Excel with Age as the independent variable and AssessmentValue as the dependent variable. Insert the bivariate linear regression equation and r^2 in your graph. Do you observe a linear relationship between the 2 variables? |
| 1280 | 2 | 1 | 31 | 671 | | Use Excel’s Analysis ToolPak to conduct a regression analysis of Age and Assessment Value. Is Age a significant predictor of AssessmentValue? |
| 4880 | 3 | 2 | 42 | 1678 | | Construct a multiple regression model. |
| 1620 | 1 | 2 | 35 | 710 | | Use Excel’s Analysis ToolPak to conduct a regression analysis with AssessmentValue as the dependent variable and FloorArea, Offices, Entrances, and Age as independent variables. What is the overall fit r^2? What is the adjusted r^2? |
| 1820 | 2 | 1 | 17 | 678 | | Which predictors are considered significant if we work with α=0.05? Which predictors can be eliminated? |
| 4530 | 2 | 2 | 5 | 1585 | | What is the final model if we only use FloorArea and Offices as predictors? |
| 2570 | 2 | 1 | 13 | 842 | | Suppose our final model is: |
| 4690 | 2 | 2 | 45 | 1539 | | AssessedValue = 115.9 + 0.26 x FloorArea + 78.34 x Offices |
| 1280 | 1 | 1 | 45 | 433 | | What wouldbe the assessed value of a medical office building with a floor area of 3500 sq. ft., 2 offices, that was built 15 years ago? Is this assessed value consistent with what appears in the database? |
| 4100 | 3 | 1 | 27 | 1268 | | Submit your assignment in Excel. Answer all questions in the Excel workbook. Please do not submit a separate Word document. |
| 3530 | 2 | 2 | 41 | 1251 |
| 3660 | 2 | 2 | 33 | 1094 |
| 1110 | 1 | 2 | 50 | 638 |
| 2670 | 2 | 2 | 39 | 999 |
| 1100 | 1 | 1 | 20 | 653 |
| 5810 | 4 | 3 | 17 | 1914 |
| 2560 | 2 | 2 | 24 | 772 |
| 2340 | 3 | 1 | 5 | 890 |
| 3690 | 2 | 2 | 15 | 1282 |
| 3580 | 3 | 2 | 27 | 1264 |
| 3610 | 2 | 1 | 8 | 1162 |
| 3960 | 3 | 2 | 17 | 1447 |
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attachment_1update.xlsx
