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week5.docxWk 5 - Apply: Regression Modeling [due Mon]
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Assignment Content duy May 21
1.
Top of Form
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 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 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 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?
Submit your assignment.
Resources
· Center for Writing Excellence
· Reference and Citation Generator
Wk
5
-
Apply: Regression Modeling [due Mon]
Assignment Content
duy May 21
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 abo
ut the tax assessment value
assigned to medical office buildings in a city. The following is a list of the variables in the database:
o
FloorArea
: square feet of floor space
o
Offices
: number of offices in the building
o
Entrances
: number of customer entrances
o
A
ge
: age of the building (years)
o
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.
o
Construct a scatter plot in Excel with
FloorArea
as the independent variable and
AssessmentValue
as the
dependent var
iable. Insert the bivariate linear regression equation and r^2 in your graph. Do you
observe a linear relationship between the 2 variables?
o
Use Excel’s Analysis ToolPak to conduct a regression analysis of
FloorArea
and
AssessmentValue
. Is
FloorArea
a signi
ficant predictor of
AssessmentValue
?
o
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?
o
Use Excel’s Analysis ToolPak to conduct a regression analysis of Age and Assessment Value. Is
A
ge
a
significant predictor of
AssessmentValue
?
Construct
a multiple regression model.
o
Use Excel’s Analysis ToolPak to conduct a regression analysis with
AssessmentValue
as the dependent
variable and
FloorArea
,
Offices
,
Entrances
, and
Age
as independent va
riables. What is the overall fit r^2?
What is the adjusted r^2?
o
Which predictors are considered significant if we work with α=0.05? Which predictors can be
eliminated?
o
What is the final model if we only use
FloorArea
and Offices as predictors?
o
Suppose our
final model is:
o
AssessedValue
= 115.9 + 0.26 x
FloorArea
+ 78.34 x
Offices
o
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 a
ppears in the database?
Submit
your assignment.
Resources
Wk 5 - Apply: Regression Modeling [due Mon]
Assignment Content duy May 21
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:
o FloorArea: square feet of floor space
o Offices: number of offices in the building
o Entrances: number of customer entrances
o Age: age of the building (years)
o 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.
o 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?
o Use Excel’s Analysis ToolPak to conduct a regression analysis of FloorArea and AssessmentValue. Is
FloorArea a significant predictor of AssessmentValue?
o 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?
o 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.
o 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?
o Which predictors are considered significant if we work with α=0.05? Which predictors can be
eliminated?
o What is the final model if we only use FloorArea and Offices as predictors?
o Suppose our final model is:
o AssessedValue = 115.9 + 0.26 x FloorArea + 78.34 x Offices
o 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?
Submit your assignment.
Resources
