Question Description
Help me study for my Data Analytics class. I’m stuck and don’t understand.
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 ?=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?
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Explanation & Answer
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FloorArea (Sq.Ft.)
4790
4720
5940
5720
3660
5000
2990
2610
5650
3570
2930
1280
4880
1620
1820
4530
2570
4690
1280
4100
3530
3660
1110
Offices
4
3
4
4
3
4
2
2
4
2
3
2
3
1
2
2
2
2
1
3
2
2
1
Entrances
2
2
2
2
2
2
1
1
2
1
2
1
2
2
1
2
1
2
1
1
2
2
2
Age
8
12
2
34
38
31
19
48
42
4
15
31
42
35
17
5
13
45
45
27
41
33
50
AssessedValue ($'000)
1796
1544
2094
1968
1567
1878
949
910
1774
1187
1113
671
1678
710
678
1585
842
1539
433
1268
1251
1094
638
2670
1100
5810
2560
2340
3690
2
1
4
2
3
2
2
1
3
2
1
2
39
20
17
24
5
15
999
653
1914
772
890
1282
3580
3610
3
2
2
1
27
8
1264
1162
3960
3
2
17
1447
Reg
Reg
Construct a scatter plot in Excel with FloorArea as the independent variable and AssessmentValue as the dependent variabl
Insert the bivariate linear regression equation and r^2 in your graph. Do you observe a linear relationship between the 2
variables?
AssessedValue ($'000)
y = 0.3067x + 162.66
R² = 0.9377
Assessed Value (In Thousands)
2500
2000
1500
1000
500
0
0
1000
2000
3000
4000
5000
6000
7000
Floor Area
Use Excel’s Analysis ToolPak to conduct a regression analysis of FloorArea and AssessmentValue . Is FloorArea a significant
AssessmentValue ?
SUMMARY OUTPUT
Regression Statistics
Multiple R
0.96835821
R Square
0.93771762
Adjusted R Square 0.93564154
Standard Error
115.599304
Observations
32
ANOVA
df
Regression
Residual
Total
SS
1
6035851.9
30 400895.972
31 64...
Review
Review
