**POLS 641**

**Introductory Analysis of Political Data**

**Fall 2008**

**Professor Mikel Wyckoff**

**Zulauf**** 403
753-7056**

**Office Hours: M 1:30 - 3:30**

This course provides an introduction to basic statistical methods
frequently encountered in the social sciences. Topics we will cover include:
(1) descriptive statistics (for example, means and standard deviations); (2)
statistical inference (random sampling and hypothesis testing); and (3)
measures of relationship and association. Students will also get an
introduction to SPSS for Windows, a widely used data analysis program.

Although I personally enjoy statistical methods very much, as a realist
I suspect that at least some of you approach this class with something less
than enthusiasm. Let me assure everyone that the course is not *that* difficult (almost everyone who is
willing to put in the time and effort can expect to earn a respectable grade).
Let me suggest, furthermore, that if you give the material a fair chance it is
likely that you will find these research tools useful (at the very least) and
even a tiny bit interesting. For those experiencing genuine fear and anxiety,
the textbook's section on Overcoming Math Anxiety may be helpful.

**REQUIRED **

The following books are required and should be available at local
bookstores. If not, they are readily available from online sources.

·
John H. Kranzler, *Statistics for the Terrified*, Prentice
Hall, 4^{th} ed., 2007.

·
Michael S. Lewis-Beck, *Applied Regression: An Introduction*,

**OTHER POTENTIALLY USEFUL **

In this course we will compute a few problems by hand but we will
primarily make use a statistical software package called SPSS when we analyze
data. Over the years, SPSS has become increasingly user friendly and I believe
that all of you can learn the basics of the program simply by watching my
demonstrations in class. Those who wish to become even more proficient at using
SPSS, however, may wish to consult one of the following guides:

·
Philip H. Pollock III, *An** SPSS Companion to Political Analysis*, CQ Press, 2008.

·
Marija Norusis, *SPSS 16.0
Guide to Data Analysis*, 2/E, Prentice Hall, 2009.

**OTHER REQUIREMENTS**

__Exams__. There
will be three examinations--two midterms and a final. Together the three exams
will constitute 70% of your final grade, with Exams 1 and 2 worth 20% each and
cumulative Exam 3 worth 30%. A small component of each exam (typically dealing
with definitional issues) will be closed book, closed notes, but when working
data analysis problems you are welcome to consult your textbook and your notes
if need be. An inexpensive electronic calculator will probably be useful when
taking the exams.

__Computer Exercises__. The
remaining 30% of your grade will be determined by your performance on computer
assignments which will require the use of SPSS statistical software available
in the main SOCQRL (in DuSable Hall) and in the SOCQRL
satellite lab that we have on the first floor of Zulauf
(course fees enable you to use these well-furnished labs). No one should feel
intimidated by these assignments. No prior knowledge of statistics is required,
the software is user friendly, and experienced lab assistants will be available
(especially in the main SOCQRL) to help with the assignments when needed. Of
course, all students must do their own assignments. This means learning to use
the required software on your own, conducting your own analyses, obtaining your
own output, and writing your own reports.

__Take-Home Problems__.
Throughout the semester I will assign sets of problems for you to work outside
of class. I expect you to do these problems, and we will spend a good deal of
time on them in class, but I will not collect them and grade them. Similar
computational problems will appear on the midterm and final exams, so devoting
significant time to the take-home problems is well justified despite the fact
that they will not be graded.

**COURSE OUTLINE AND READING
ASSIGNMENTS**

**I. PART ONE: Descriptive
Statistics**

·
Introduction and basic math review Kranzler, Appendix A
and Ch. 1-2.

·
Introduction to SPSS

·
Variables, Levels of Measurement, Frequency
Distributions

·
Measures of Central Tendency and Variation

·
The Normal Distribution

·
Percentiles and Standardized Scores

__EXAM I__**:
Tuesday, September 30**

**II. PART TWO: Data Analysis Using Independent Variables To
Explain Dependent Variables**

**A. Analyzing Categorical Data
with Crosstabs**

1. Introduction to crosstabs; relationships and measures of association

·
The Crosstabs Procedure. Reading TBA.

·
Measures of Association for Nominal and Ordinal
Data. Reading TBA.

2. Hypothesis testing (significance testing) with crosstabs; holding
third variables constant

·
Random Sampling, Inferential Statistics and the
Concept of a Sampling Distribution

·
Hypothesis Testing I:
The chi-square test

·
Using Control Variables with Crosstabs Reading TBA.

**B. Analyzing Interval Level
Dependent Variables and Categorical Independent Variables**

1. The t-test Analyzing
differences of means observed in two groups

·
Additional Thoughts on Sampling Distributions;
Standard Errors.

·
Hypothesis Testing II: The t-test

2. ANOVA (Analysis of Variance) Analyzing differences of means observed in
three or more groups

·
Hypothesis Testing III: The F-test and Analysis
of Variance

__EXAM 2__: Tuesday, November 11

**C. Analyzing Two or More
Continuous Variables Bivariate
and Multivariate Regression Analysis**

·
Measures for interval data: Pearsons r and
the slope of the regression line

·
Significance tests and confidence intervals Lewis-Beck, pp. 30-37.

·
Multivariate analysis Lewis-Beck, pp. 47-58.

·
Dummy variable analysis Lewis-Beck, pp. 66-71.

__EXAM 3__: Thursday, December 11,