Instructions: The Excel file for this assignment contains a database with information about the tax assessment...
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Instructions: 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: • FloorArea: square feet of floor space • Offices: number of offices in the building Entrances: number of customer entrances • Age: age of the building (years) • AssessedValue: tax assessment value (thousands of dollars) Use the data to construct a model that predicts the tax assessment value assigned to medical office buildings with specific characteristics. • 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? • Use Excel's Analysis ToolPak to conduct a regression analysis of FloorArea and Assessmentvalue. Is FloorArea a significant predictor of Assessmentvalue? • 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? • Use Excel's Analysis ToolPak to conduct a regression analysis of Age and Assessment Value. Is Age a significant predictor of Assessmentvalue? Construct a multiple regression model. • 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? • Which predictors are considered significant if we work with a=0.05? Which predictors can be eliminated? • What is the final model if we only use FloorArea and Offices as predictors? • Suppose our final model is: • AssessedValue = 115.9 + 0.26 x FloorArea + 78.34 x Offices • 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? FloorArea (Sq.Ft.) Offices Entrances Age AssessedValue ($'000) 4790 4. 2 8 1796 4720 3 2 12 1544 5940 4. 2. 2 2094 5720 4 34 1968 3660 2. 38 1567 5000 4. 31 1878 2990 1 19 949 2610 48 910 5650 4. 42 1774 3570 1 4 1187 2930 2 15 1113 1280 2 1 31 671 4880 3 42 1678 1620 1 2 35 710 1820 2 17 678 4530 2 5 1585 2570 2 1. 13 842 4690 45 1539 1280 1 1 45 433 4100 1 27 1268 3530 2 41 1251 3660 33 1094 1110 1 50 638 2670 2 39 999 1100 1 1 20 653 5810 4. 3 17 1914 2560 24 772 2340 890 3690 15 1282 3580 2 27 1264 3610 1 8 1162 3960 17 1447 Instructions: 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: • FloorArea: square feet of floor space • Offices: number of offices in the building Entrances: number of customer entrances • Age: age of the building (years) • AssessedValue: tax assessment value (thousands of dollars) Use the data to construct a model that predicts the tax assessment value assigned to medical office buildings with specific characteristics. • 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? • Use Excel's Analysis ToolPak to conduct a regression analysis of FloorArea and Assessmentvalue. Is FloorArea a significant predictor of Assessmentvalue? • 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? • Use Excel's Analysis ToolPak to conduct a regression analysis of Age and Assessment Value. Is Age a significant predictor of Assessmentvalue? Construct a multiple regression model. • 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? • Which predictors are considered significant if we work with a=0.05? Which predictors can be eliminated? • What is the final model if we only use FloorArea and Offices as predictors? • Suppose our final model is: • AssessedValue = 115.9 + 0.26 x FloorArea + 78.34 x Offices • 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? FloorArea (Sq.Ft.) Offices Entrances Age AssessedValue ($'000) 4790 4. 2 8 1796 4720 3 2 12 1544 5940 4. 2. 2 2094 5720 4 34 1968 3660 2. 38 1567 5000 4. 31 1878 2990 1 19 949 2610 48 910 5650 4. 42 1774 3570 1 4 1187 2930 2 15 1113 1280 2 1 31 671 4880 3 42 1678 1620 1 2 35 710 1820 2 17 678 4530 2 5 1585 2570 2 1. 13 842 4690 45 1539 1280 1 1 45 433 4100 1 27 1268 3530 2 41 1251 3660 33 1094 1110 1 50 638 2670 2 39 999 1100 1 1 20 653 5810 4. 3 17 1914 2560 24 772 2340 890 3690 15 1282 3580 2 27 1264 3610 1 8 1162 3960 17 1447
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Construct a scatter plot in Excel with Floor Area as the independent variable and Assessment Value a... View the full answer
Related Book For
Accounting Information Systems
ISBN: 978-1133935940
10th edition
Authors: Ulric J. Gelinas, Richard B. Dull
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