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University of Maryland                                                                 Spring 2007

School of Public Policy                                                                  PUAF 610

 

 

 

 

 

 

 

 

 

 

QUANTITATIVE ANALYSIS

 

 

Instructor:                     Michael Busse

                                                Mbusse@umd.edu

                                                Busse340301@aol.com

                                                TA session:                   Monday: 7-9

 

                                                ______________________________________________________________________________

           

            This course introduces students to quantitative analysis with special application to issues of public policy.  We will begin with definitions of basic statistical terms and finish with an introduction to linear regression. Though this class will require some math, it will also emphasize interpreting results and understanding how the techniques we study apply to policy analysis.

 

. A problem set will be assigned for nearly every class, and will be due at the beginning of the following class.  When possible, students are persuaded when possible to work together on problem sets. Doing the problem sets and applying what we learn to every day materials such as the Washington Post, the Economist, etc will be more useful than studying the text if your time is short. 

 

Evaluation in the course will be based on problem sets, a midterm, a final exam, and classroom participation. Exams will include only topics covered in class or on problem sets. The book has additional information and is a good backup. 

 

                                                Class Participation        10%

                                                Problem Sets                30%

                                                Midterm                       25%

                                                Final                             35%

 

 

 

 

 

 

TOPICS AND READINGS: Spring 2007

 

 

 

            Date                                        Topic                                                   Readings

 

1.  Jan 24                                              Introduction +Summary Statistics                                                           

                                                            Experimental Design

 

2.  Jan 31                                              Probability & Bayes Rule                                                                                                                                              

3.  Feb 7                                               Probability & Bayes Rule +Sampling     

                                                                                               

4.   Feb 14                                            Probability Distributions:Binomeal          

                                                            Normal

5.   Feb 21                                                        Sampling: Central Limit Theorem           

6.   Feb 28                                            Estimation and Confidence Intervals      

                                                                                                                                                                                   

7.      Mar 7                                             Hypothesis Testing                                                                               

                                                                                                                       

8.      Mar 14                                           Midterm                                               

 

                                                                                                                       

9.       Mar 28                                                          Population Proportions                          

 

10.   Apr 4                                                          Simple Liner Regression                                   

 

11.   Apr 11                                                        Simple Linear Regression                      

 

12.   Apr 18                                                          Multiple Regression     

 

 

13.   Apr 25                                            Chi Square Tests                                  

 

14.   May  2                                            Logit and Probit                        

 

15.   May 9                                                            Final Presentations

 

                                                                                           

May 12-18                                            Final Examination