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Homework answers / question archive / Assignment Content Purpose  This assignment provides an opportunity to develop, evaluate, and apply bivariate and multivariate linear regression models

Assignment Content Purpose  This assignment provides an opportunity to develop, evaluate, and apply bivariate and multivariate linear regression models

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Assignment Content

  1. Purpose 
    This assignment provides an opportunity to develop, evaluate, and apply bivariate and multivariate linear regression models.


    Resources: Microsoft Excel®, DAT565_v3_Wk5_Data_File


    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 FloorAreaOfficesEntrances, 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 α=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 would be 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?
    • Submit your assignment. 

Regression Modeling Data

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 2 34 1968
3660 3 2 38 1567
5000 4 2 31 1878
2990 2 1 19 949
2610 2 1 48 910
5650 4 2 42 1774
3570 2 1 4 1187
2930 3 2 15 1113
1280 2 1 31 671
4880 3 2 42 1678
1620 1 2 35 710
1820 2 1 17 678
4530 2 2 5 1585
2570 2 1 13 842
4690 2 2 45 1539
1280 1 1 45 433
4100 3 1 27 1268
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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