Regression Assignment for Statistics for Business

Statistics for Business II Regression Assignment

Due: Tuesday, April 1 8, 201 7 by 6 :00pm

No late assignments will be accepted. NO EXCEPTIONS!

READ ALL INSTRUCTIONS!

You must turn in your regression assignment by 6:00pm on April 18, 2017 to the CourseDen

assignment folder (formerly called “dropbox ”). Requests to turn in the regression assignment

after this time will be denied . NO EXCEPTIONS ! DO NOT EMAIL ANY FILES TO ME. Only

assign ments submitted to the CourseDen assignment s folder (formerly called “dropbox ”)

will be graded. It is your responsibility to ensure you have submitted the file you wish to

have graded. If you upload an incorrect file, you will NOT be allowed to resubmit the file

after the deadline has pa ssed, and your grade for the assignment will be based on the

assignment submitted to the CourseDen folder.

Final assignment submissions should be clearly labeled and neatly organized. Answers should be labeled using

the question number and letter (f or example, 1a) and should be in the same order as the questions. Each Excel

worksheet must be clearly labeled. Poin ts will be deducted for assignments that are not neatly put together or

for answers not clearly labeled .

You are to work on this assignment individually. Students who turn in the same /similar

assignment s will each receive a grade of zero. These students will also be reported to the

Student Conduct Office for violation of the Academic Honor Code.

Please Note:

Emailed ass ignments will NOT be accepted. If you have trouble uploading your completed

ass ign ment to the CourseDen assignment folder (formerly called “dropbox ”) or have questions

regarding the file y ou have submitted , you must notify me in writing no later than 2:00 pm on

the scheduled due date, failure to do so will result in a grade of ze ro if the assignment is not

turned in to the dropbox (assignment) folder by the deadline.

You should ensure that your Excel file is saved properly and can be reopened for grading. If

you are unsure that your file has been saved properly, you should notify me no later than

2:00 pm on the scheduled due date. Once the deadline has passed, i f I cannot open your

submitted Exce l file for grading, a grade of zero will be given and no resubmission will be

allowed .

IT IS YOUR RESPONSIBILITY TO SUBMIT THE FILE YOU WISH TO HAVE

GRADED BEFORE THE SUBMISSION DEADLINE. ONLY FILES SUB MITTED TO

THE COURSE DEN ASSIGNMENTS FOLDER (formerly called “dropbox ”) WILL BE

GRADED. NO RESUBMISSIONS WILL BE ALLOWED FOR ANY REASON. NO

EXCEPTIONS!

Read and follow all instructions before beginnin g your assignment.

Failure to follow instructions will result in a loss of points.

Question 1 : In this assignment you are provided with data from a research paper by Ella Hartenian and

Nicholas Horton, who examined whether or not there was a relationship between rail trails a nd property

values in Northamp ton, MA. The da ta are located in the file `house prices.xlsx' which is in you r e -mail on D2L

(course den email) . Please see the accompanying word document, `documentation.docx,' which describes

what each of the columns in the data set mean and how they are scaled. For th is assignment you will learn

how to estimate a common regression model used in economics, finance , and real estate called a “ hedonic

price model."

1. Create a copy of the data set by right -clicking the tab at the botto m and clicking `Move or Copy...’, then

create another copy of the data set in the same workbook. Label this copy “Modified Data" and the original

tab “ Original Data." N ow click on the tab for “Modified Data." Delete all variables except `price2014,'

`bedrooms,' `garage space', `nofullbath', ` norooms', `squarefeet,' and `walkscore.' You should have seven

total variables.

(a) M ake sure `price 2014' is the far l eft variable, then estimate the model where `price2014' is a function

of the other six variables .

(b) For each variable, explain what the sign of the regression coefficient was, what the magnitude was

(i.e., if x goes up by one unit how much does y increase by), and whether or not the results of your

regr ession were consistent with what you believed the sign and magnitude to be. Then explain if any

variables were insignificant.

value for each of your six explanatory variables using the AVERAGE() function in Excel. Finally, make a

prediction for the price if each of the variables take their average value.

(d) Explain briefly if there are any variables in the data set you think should have been included and, i f so,

why.

Question 2 : In this assignment you are provided with data from a research paper by Ella Hartenian and

Nicholas Horton, who examined whether or not there was a relationship between rail trails a nd property

values in Northamp ton, M A. The data are located in the fi le `house prices.xlsx' which is in you r e -mail on D2L

(course den email) . Please see the accompanying word document, `documentation.docx,' which describes

what each of the columns in the data set mean and how they are scaled. For this assi gnment you will assess

whether rail trails in fluence property values.

2. Create a copy of the data set by right -clicking the tab at the bottom and clicking `Move or Copy...’, then

create another copy of the data set in the same workbook. Label this copy “M odified Data" and the original

tab “ Original Data." Now click on the tab for “Modifi ed Da ta 2." Delete all variables you consider to be

irrelevant to the price of a house. Make sure `price2014' is the far left variable. Then answer the questions:

(a) Estimate the model where house prices are affected by rail distance only. What is the sign and

magnitude of the coefficient on rail distance, and what is the fit of the regression?

(b) Estimate a new model where house prices are affected by both ra il distance and previ ous prices. What

is the sign and magnitude of the coefficient on rail distance, and what is the fi t of the regression?

well as any other variable you consid er relevant. What is the sign and magnitude of the co efficient on

rail distance, and what is the fit of the regression?

(d) Write a paragraph tha t answers whether rail trails aff ect housing prices based on your three models.