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PART A). Excel Project Instruction
To answer these questions, you first need
to look at the attached Excel File and, after some required manipulations,
which will entail using Excelâs Formula and other functions, you are to run a
model using Excelâs Multiple Regression feature.
You are to type your answers here in MS
Word and, wherever needed, copy & paste the information (Numbers or graphs)
form Excel print outs of the Regression Results to this Word File.
The First part has to do with you
manipulate the data and run the regression and saved that as an Excel File and
turn it in; you will see below what operations you should perform in Excel.
Save this file
as:
âExcel Output-Your Nameâ Example: Excel Project- Bart Simpson
and deliver them via Blackboard. Do not forget to Include, on the top of Excel output, YOUR NAME and YOUR MAJOR.
The second part,
Part B (A MS Word file) contains the regression Questions). It should be typed, saved and submitted via
Bb.
Save This File as:
âExcel
Project Answers- Your Nameâ
Each Part (Parts A & B), have 100 pints
for a total of 200 points for this Excel Project.
The attached file (Excel Project
data) is a sample data where Y is modeled as a function of X1, X2,
X3,and X4. That
is:
y = Æ(X1,
X2, X3,X4).
The linear model
specified is as follows:
y = ?o + ?1X1 + ?2X2 + ?3X3
+?3X4 +?
Based on the
sample data, you are to Run a Multiple Regression model in Excel to estimate
the values of the parameters (b0 , b1 ,b2 ,b3 and b4) for
the following Estimator equation:
?=b? +b1X1 +b2X2 +b3X3 +b3X4
PART A)–MANIPULATION OF THE
EXCEL DATA SET (100 Points)
A1.First
of all, you see that, instead of the familiar COLUMNS of the independent
variables, here, you have ROWS of them.
You are to use Excelâs Transposefeature to create a data set with columns,
instead of rows (You probably know that Excel
really does not need the transpose to
run Regression Model, but I AM ASKING YOU to do it!)
A2. As you can see in the attached Excel file, you do not have a column for
the fourth independent variable in the model above (X4).
YOU are to
create that column next to column for column X3. Now, Variable X4 , is the Natural Logarithm (Base e) of the Mean of
columns X2 and X3,. Then get the Natural Log of that Mean You are
to create this column, using appropriate Excel functions.
A3. After
creating the column for X4,you run the Multiple Regression where y
is your dependent variable and X1,
X2, X3,and X4b
are your Dependent variables. Ask
for Residuals, and residual plots and Normal . Probability Plot.
A5. YOU should also create the Correlation Matrix of the independent
variables in this NEW data set using
Excelâs relevant statistical function.
You have questions below that will require use of that matrix.
A6. You
should know how to calculate the Durbin-Watson Statistic (Formula below as well
as in Formula sheet) and you should also know for what purpose Durbin-Watson
Statistic and Correlation Matrix is used.
You are asked to calculate the Durbin-Watson statistics. Here is the formula
for D-W Test Statistics (Also included in the Formula Sheet 2):
Durbin-Watson Test
Statistics
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A7. You also need to create the
Histogram of the residuals so that you answer the related question(s) in Part B.
You may have to extend the height of
your Histogram Chart to make it more visible.
PART B). This part is
also included in Bb as a separate part called Final, you should use THAT file to answer the
questions based on your Excel work and do not use that below.
Now, based on your
Excel output, answer the following questions about Multiple Regression. As you know, for some of these questions, you
have to copy & paste here, from Excel output, the relevant numbers or
charts.
Since you have
already created the Excel Output, copy and paste any part that you need t use
to give our answer, from Excel to this Document.
Here are the
questions:
Note: In all
Questions, where-ever needed, use the 5% level of significance to test the
hypotheses (?=0.05).
B1.What is the Sample Regression Equation?
B2. Which
of the Independent variables are significant?
Why? Explain. Use? = 0.05 in ALL
questions.
Use only the p-value to explain your answers.
B3. Test the
overall significance of the model by conduction an F test. Demonstrate the Hypothesis you are testing.
B4. What is the value of adjusted r-square.
Verify its value, using the formula for adjusted r-square and using the values
in your Excel Printout.
B5. Comment on
the Normality assumption for the residuals for this model. In other word, has the normality assumption
been satisfied? Explain your answer
(Hint: you need to run Excelâs Histogram feature for Column of the Residuals).
B6. Do
you see any indication of Multicollinearity?
Explain why. (Hint: Run the
Correlation Matrix of the Independent Variables). Can you find any evidence of
Multicollinearity without referring to the Correlation Matrix? Explain.
B8. Do you see
any indication of Heteroscedasticity for the Variable X4? Copy and paste the residuals for this
variable only. Demonstrate and Explain
why.
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