It is a Final project in Advanced Statistics, please let me know if you are willing to do it.

Advanced Statistics (STA 327 AB)

Final Project Version B

What Determines the Price of a House?

Due on May 2nd, 2021

Spring 2021

Use Excel to Run All the Regressions and Show All Your Work:

What determines the price of a house? Is it the size of the house, the size of the yard, having a central air condition in the house, or all these factors combined? Using the “Housing Prices Data” file posted on Campus Web, write a 3-to-5-page project addressing this question. Make sure to include the following:

1. Run a regression of the price of the house on the size of the house and answer the following questions:

1. Write down your estimated equation.

2. Are your estimated coefficients significant? Explain.

3. According to your estimate, what is the predicted price of a 2000-square-foot house?

4. According to your estimate, what is the predicted change in the price of the house if its size increases by 100 square feet?

5. Does the size of the house account for a large fraction of the variation in the price of the house?

1. Run a regression of the price of the house on whether the house has a central air condition and answer the following questions:

1. Write down your estimated equation.

2. Are your estimated coefficients significant? Explain.

3. According to your estimate, what is the predicted price of a house with a central air condition?

4. According to your estimate, what is the predicted price of a house without a central air condition?

5. What is the value of in your model? What does it mean?

1. Run a regression of the price of the house on the size of the house and the size of the yard, and answer the following questions:

   1. Write down your estimated equation.

   2. Are your estimated coefficients significant? Explain.

   3. According to your estimate, what is the predicted price of a 1500-square-foot house with a 5000-square-foot yard?

   4. According to your estimate, what is the predicted price of a 2200-square-foot house with a 7000-square-foot yard?

   5. What is the value of in your model? What does it mean?

1. Run a regression of the price of the house on the size of the house, the size of the yard, and whether the house has a central air condition, and then answer the following questions:

   1. Write down the estimated equation.

   2. What does each estimated coefficient mean?

   3. According to your estimate, what is the predicted price of a 2000-square-foot house with a 6000-square-foot yard and a central air condition?

   4. According to your estimate, what is the predicted price of a 2000-square-foot house with a 6000-square-foot yard and no central air condition?

   5. What is the value of in your model? What does it mean?

   6. Compare of this model to you obtained in the first two regressions and explain why they are different.

   7. What is the value of adjusted in your model?

   8. Using the F-test, test the significance of the model: Are all your explanatory variables significant?

   9. Using the t-test, test the hypothesis that each of your individual variable is significant.

General Comments:

Make sure while you are writing your final project to include the following:

• Start with a short introduction to explain the purpose of the project. Explain to a general reader what this project is all about.

• Mention the data and the variables used, specifically binary (dummy) variables. Make sure to include the units of measurements used for each variable.

• Explain the methodology used in your analysis and the software used to run the regressions.

• Report the estimated equations the proper way.

• Make sure you interpret the coefficients of each regression.

• Make sure the final project is smoothly read, i.e. don’t simply answer the questions. Answer the questions in a smooth way so that the project is a short paper.

• In the end, include a short conclusion in which you compare all the models.

STA327 Final Project

F. Raouf

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