George Mason University – Graduate Council
Graduate Course Approval Form
All courses numbered 500 or above must be submitted to the Graduate Council for final approval after approval by the
sponsoring College, School or Institute.
Graduate Council requires submission of this form for a new course or any change to existing courses. For a new course,
please attach a copy of the syllabus and catalog description (with catalog credit format, e.g. 3:2:1). The designated
representative of the College, School or Institute should forward the form along with the syllabus and catalog description,
if required, as an email attachment (in one file) to the secretary of the Graduate Council. A printed copy of the form with
signatures and the attachments should be brought to the Graduate Council meeting. Please complete the Graduate Course
Coordinator Form if the proposed changes will affect other units.
Note: Colleges, Schools or Institutes are responsible for submitting new or modified catalog descriptions (35 words or
less, using catalog format) to Creative Services by deadlines outlined in the yearly Catalog production calendar.
Please indicate: New X
Modify
Delete
Department/Unit: Public and International Affairs
Course Subject/Number: GOVT 712
Submitted by: Ann Ludwick
Ext: 3707
Email: aludwick
Course Title: Problem Solving and Data Analysis II
Effective Term (New/Modified Courses only): 200870
Credit Hours: (Fixed) 3
(Var.)
to
Final Term (deleted courses only):
Grade Type (check one): x
Repeat Status*(check one): x NR-Not repeatable
term
RD-Repeatable within degree
*Note: Used only for special topics, independent study, or internships courses
Regular graduate (A, B, C, etc.)
Satisfactory/No Credit only
Special graduate (A, B, C, etc. + IP)
RT-Repeatable within
Total Number of Hours Allowed:
Schedule Type Code(s): 1. LEC LEC=Lecture SEM=Seminar STU=Studio INT=Internship
IND=Independent Study
2.
LAB=Lab RCT=Recitation (second code used only for courses with Lab or
Rct component)
Prereq x
Coreq
(Check one): Prerequisite:
GOVT 711
_________________________________________________________________________________________
Note: Modified courses - review prereq or coreq for necessary changes; Deleted courses - review other courses to correct prereqs that list the deleted course.
Description of Modification (for modified courses):
Special Instructions (major/college/class code restrictions, if needed):
Department/Unit Approval Signature:_________________________________________ Date: _____________
College/School Committee Approval Signature:__________________________________ Date:_____________
Graduate Council Approval Date:____________ Provost Office Signature:_________________________________
George Mason University
Graduate Course Coordination Form
None needed
Approval from other units:
Please list those units outside of your own who may be affected by this new, modified, or deleted course. Each
of these units must approve this change prior to its being submitted to the Graduate Council for approval.
Unit:
Head of Unit’s Signature:
Date:
Unit:
Head of Unit’s Signature:
Date:
Unit:
Head of Unit’s Signature:
Date:
Unit:
Head of Unit’s Signature:
Date:
Unit:
Head of Units Signature:
Date:
Graduate Council approval: ______________________________________________ Date: ____________
Graduate Council representative: __________________________________________
Date: ____________
Provost Office representative: ____________________________________________
Date: ____________
Govt 712 PROBLEM SOLVING AND DATA ANALYSIS II
Introduction
This course provides students with a deeper understanding of a range of quantitative techniques-derived from the fields of economics, management and statistics--that can readily be applied by public-sector
researchers and decision-makers. Students will develop an understanding of the: 1) quantitative principles
underlying these techniques, 2) appropriate application(s) of each technique, 3) interpretation and use of the
findings of each and, 4) limitations of the various statistical approaches and their results. In-class and at-home
problems designed to foster students' understanding of these principles, applications, and interpretations will
be assigned throughout the semester. Clear and concise written presentations of problems, proposed
solutions, and final results will be emphasized throughout the course.
Requirements and Grading
Students are expected to complete--prior to class meetings--all assigned readings, assignments, and
examinations. All assignments and examinations are to be submitted on paper rather than electronically,
Grades will be based upon: 1) four (4)-homework assignments (30%), 2) a take-home mid-term
examination (30%) and, 3) a take-home final examination (40%).
Materials for Exams and Assignments
At-home assignments as well as the mid-term and final exam may incorporate computer-based
activities drawn from the SPSS software. Materials covered in the examinations will be drawn from the
required Norusis textbook, course materials found on WebCT, journal articles (available on-line through
GMU’s JSTOR connection), classroom lectures, and homework assignments.
In-class computing exercises are also incorporated into the course to familiarize students with the data
manipulation and calculation capabilities and statistical reporting of the SPSS statistical software and,
accordingly, to enable students to meet (or exceed) course requirements. Assigned readings and solutions to
at-home exercises will be discussed in class.
Late Assignments and Grades of Incomplete
Assignments are due at the beginning of class on the scheduled due date and are generally graded on a
0-10 point scale. Assignments are to be printed rather than electronic (email). Electronic submissions establish
that an assignment was completed on time, but students will not receive a grade until the paper version is
submitted at the next class meeting. Late assignments will be accepted, but grades will be discounted at the
rate of 1 point/day. Grades of Incomplete require written application to the Instructor at least 24 hours before
the scheduled date of the final exam. Applications must include: reason for request, course work completed to
date, and a schedule for completing all course work.
Honor Code
Students are expected to comply with the Honor Code of George Mason University. Please refer to the
University’s Honor Code website: http://honorcode.gmu.edu/
Textbook
SPSS 14.0 or SPSS 13.0, Guide to Data Analysis, Marija J. Norusis; Prentice Hall (2005).
Statistical Software
SPSS 13.0 or SPSS 13.0 Student Version for Windows
Recommended Readings
Regression with Graphics: A Second Course in Applied Statistics, L. C. Hamilton, Duxbury Press (1991).
The Chicago Guide to Writing about Numbers, Jane E. Miller, The University of Chicago Press (2004).
Multivariate Statistical Analysis: A Conceptual Introduction (2nd edition), Sam Kash Kachigan, Radius Press
(1991)
Govt 712
Week 1
RESEARCH DESIGN, CONFIDENCE INTERVALS, T-test, Analysis of Variance
--Go to http://www.execpc.com/~helberg/pitfalls/ and read Pitfalls of Data Analysis
(or How to Avoid Lies and Damned Lies)
--Read the Bureau of Transportation Statistics’ Guide to Good Statistical Practice in the
Transportation Field.
http://www.bts.gov/publications/guide_to_good_statistical_practice_in_the_transportation_field/
--Norusis, Chs. 11, 14 – 16 (Difference of Means (or, T) tests & Analysis of Variance)
Week 2
CORRELATION & BIVARIATE REGRESSION REVIEW
--Norusis, Ch. 20 (Bivariate Regression)
--Read WebCT materials on Reg_612_Revu and Reg_Assumptions BEFORE CLASS
--Read Gary King’s "How Not to Lie with Statistics: Avoiding Common Mistakes in
Quantitative Political Science (search--via the GMU Library connection for author
or title at http://www.jstor.org)
Week 3
BIVARIATE REGRESSION: HYPOTHESES TESTING & RESIDUAL ANALYSIS
--Norusis, Chs. 21 & 22
--Read WebCT materials on Regression_612 and Reg_Assumptions BEFORE CLASS
Week 4
INTRODUCTION TO MULTIPLE REGRESSION
--Norusis, Ch. 23
--Read "Politics, Bureaucrats and Schools" Smith, Kevin B. and Meier, Kenneth J.,
Public Administration Review, Vol. 54, No. 6 (Nov.-Dec., 1994), 551-558.
Available on-line at JSTOR through the GMU library.
Week 5
APPLIED MULTIPLE REGRESSION ANALYSES (I)
--Norusis, Ch. 23
--Read WebCT materials on Multivariate_Output
Week 6
APPLIED MULTIPLE REGRESSION ANALYSES (II)
--Norusis, Ch. 23
--Read WebCT materials on Multivariate_Output
Week 7
TESTING MULTIPLE REGRESSION ASSUMPTIONS & RESIDUAL ANALYSIS (I)
--Norusis, Ch. 24
--Read WebCT materials on OLS Diagnostics
Week 8
TESTING MULTIPLE REGRESSION ASSUMPTIONS & RESIDUAL ANALYSIS (II)
--Norusis, Chs. 22 - 24
Week 9
RECODING & COMPUTING VARIABLES (logarithms, net present
value, "dummy" variables, interaction terms)
--Norusis, Appendix B.
--Read WebCT materials on Variable Transformations BEFORE class
Week 10
"DUMMY" VARIABLE REGRESSION MODELING
--Read WebCT materials on Dummy Variables in Regression BEFORE class.
--Read: Crewson and Fisher "Growing Older and Wiser:
The Changing Skill Requirements of City Administrators,"
Public Administration Review, Vol. 57, No. 5 (Sept. 1997), 380-386.
Available on JSTOR.
Week 11
EXTENDING OLS (I): Weighted Least Squares
--Read "Contributions, Lobbying, and Committee Voting in the U.S. House of
Representatives," Wright, John R., American Political Science Review,
Vol. 84, No. 2 (Jun. 1990), 417-438. Available on JSTOR (and difficult).
Week 12
EXTENDING OLS (II): Logit/Probit Models,
--Read: "Probing the Bounds of Conventional Wisdom: A Comparison of Regression,
Probit, and Discriminant Analysis," Aldrich, J. Cnudde, C.F., American Journal of
Political Science, Vol. 19, No.3, (Aug. 1975). Pp. 571-608. Available on JSTOR.
--Read: "Federal District Judges and Presidential Power During the Postwar Era,"
Ducat, C and Dudley, R., Journal of Politics, Vol. 51, No.1. (Feb., 1989) pp.98-118.
Available on JSTOR.
Week 13
MULTIVARIATE REVIEW: Assumptions, Statistical Interpretations & Residuals
Exam Date
FINAL & TAKE-HOME FINAL EXAMINATION DISTRIBUTED
College of Humanities and Social Sciences
COURSE CATALOG COPY FORM
For the revision of catalog copy for new or modified courses
On this form please provide the entry that will be used in the Course Description section of the
University Catalog.
A. Subject code number, course title, and credit hours. For example: ENGL 101 Composition
(3:3:0). In the catalog code (3:3:0), the first number indicates the total number of credits, the
second number indicates the hours of lecture of seminar per week, and the third number
indicates the hours of laboratory or studio per week.
Subject code and number: GOVT 712
Title: Problem Solving and Data Analysis II
Credit code: (3:3:0)
B. Prerequisites needed prior to registration in the course or co-requisites:
Prerequisites:
Prerequisite: GOVT 711
Co-requisites:
C. Description of the course as it will appear in the catalog. Consult the catalog for models.
(Keep descriptions concise, use verb phrase not sentences, use present tense)
Advanced techniques and skills for solving policy-related problems or analyzing political data. Focuses on data
gathering and analysis, use of statistical software and multivariate analysis.
Office of the Dean Use Only
Entered By:
Date: