INFO 5880 Research Project Regression Analysis

INFO 5880 Research Project
Regression Analysis
Let’s assume that you get a new job as a realtor. You decide to apply regression analysis
to give better guidance to your customers. The following worksheet will help you to
analyze the factors which will affect the purchase price of your customer’s dream house.
Part 1) Data Collection
Collect and code the data: We are going to collect data for the Montgomery and Auburn
area. Go to a website providing real estate data (for example, www.realtor.com,
www.zillow.com) and choose home type “houses for single family” (not an apartment,
condo, lots). We (randomly) select 30 houses from Montgomery and 30 houses from
Auburn, and save them in a file, housing_data_5880_ your name.xls. Use the following
variable description to collect the data.
1. price purchase price in $1000s
2. bdrms number of bedrooms
3. sqft size of house in square feet
4. age age of house = 2019 – year built
5. pool =1 if the house has a swimming pool
= 0 otherwise
6. city =1 if the house is located in the city of Montgomery
= 0 otherwise
From the website you may see the following facts:
Obs 1)
4 beds, 3 baths, 2762 square feet
Built in 1988
No swimming pool
Sale Price: $264,900
Address: XXXX, Montgomery, AL
Obs 2)
4 beds, 3 baths, 2222 square feet
Built in 2013
Swimming pool
Sale Price: $350000
Address: XXXX, Auburn, AL
2
The collected data set should be saved in the following format:
obs price bdrms sqft age pool city
1 264.9 =
264000/1000 4 2762 31 = 2019-1988 0 1
2 350 4 2222 4 1 0
…
Part 2) Regression Analysis with Excel
You can employ regression analysis with Excel to estimate house prices based on 60
observations.
Step 1) Describe regression analysis briefly. What is the reason that you are doing the
regression analysis? What are the things that you can figure out based on your analysis?
Step 2) Estimate the following model and answer for each question.
1. Model 1: price = ? + ?$????? + ?* ??? + ?/ ???? + ?
A couple is looking for a house and comparing prices between Montgomery and
Auburn. Specifically, they would like to know whether being located in a specific city
tends to increase or decrease the price of a house and whether the effect is statistically
significant. Provide them with some guidance based on the quantitative evidence from
your EXCEL estimation.
2. Model 2: price = ? + ?$????? + ?* ??? + ?/ ???? + ?3 ???? + ?
Assume that the couple is considering a house whose size is about 3000 square feet,
relatively new (built in 2010), located on Montgomery with a pool for their children.
They would like to know the expected price of the house. Estimate the following model
and provide them some with guidance based on the quantitative evidence from your
EXCEL estimation.
Step 3) To explain the purchasing price of the house better, what would be additional
variables that could be added to model 2? Write down the variable name and description.
3
Part 3) Report on the project
Step 1) Write-up: Submit a 4 page write-up (including 1 page of table result) to explain
the details appear in your project (Use 12 points with double spacing).
1 Problem Statement
1.1 Purpose of the project
e.g., Through this project, I would like to examine the relationship between the
purchasing price of the house and possible factors affecting the price.
1.2 Reasons for using the empirical methodology
: Describe regression analysis briefly. What is the reason that you are doing
the regression analysis? What are the things that you can figure out based on
your analysis?
2 Empirical Analysis
2.1 Data Source and Description
: Use the data correction in part 1.
2.2 Scatter Plot
: draw scatter plots between the dependent variable and the independent
variables, and discuss the relationship between the variables.
3. Application
3.1 Estimation: Effect of city
Model 1
: Discuss the situation described in the question and estimated results of
model 1 in Step 2.
3.2 Estimation: Effect of pool
Model 2
: Discuss the situation described in the question and estimated results of
model 2 in Step 2.
4. Conclusion
Summarize your empirical results concisely. What is something you did in the
project? Discuss briefly the limitation of your analysis.
: Use the result in Step 3 to discuss the limitation.
Appendix. Empirical Evidence
Include the table (copy of Excel spreadsheet) at the end of the write-up.

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