Comp Question from REAE 5350

The REAE doctoral minor comprehensive examination questions will come from the following list of candidate questions.

REAE 5350: Quantitative Methods in Real Estate Analysis

1. What is multicollinearity and why is it a problem for a) prediction/estimation, b) structural modeling?

2. Define p-value. How is the p-value used to give an indication of statistical significance?

3. Compare and contrast main effects and interaction effects. Use an example and/or graph if appropriate.

4. How does the stepwise algorithm select the next variable to be included in the model?

5. What is a sampling distribution? What are the properties of the sampling distribution of sample means? Why are these properties important to parametric estimation?

6. Explain the use of ARCH and GARCH in statistical analysis.

7. What is the error term in a simple linear regression? What is its expected value? How do we estimate the error term, and what do we call these estimates? How are these error terms used in regression analysis?

8. What are the different classifications of statistics? Explain the general characteristics of each category. Also describe the relationship between these classifications. Considering the nature of real estate data, what types of statistics are particularly useful in real estate research, and why?

9. What is autocorrelation, why is it a problem, and what is one technique for correcting the issue?

10. What is heteroscedasticity, how does it affect statistical inference, and how can it be corrected?