**POLS 641**

**Introductory
Analysis of Political Data**

**Fall 2009**

**Professor
Mikel Wyckoff**

**Zulauf
403 753-7056**

**Office
Hours: MWF 11-12:00 & by appointment**

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 ****READINGS**

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 ****READINGS**

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__**: **Monday, October 5

**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. – See handout, “How to Read a
Crosstab” that I placed in your mailbox.

·
Measures of
Association for Nominal and Ordinal Data.
– See untitled handout that I placed in

your
mailbox. For now read pp. 144-151,
starting with “Measures of Association.”

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

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

Kranzler, Ch.
10.

·
Hypothesis Testing
I: The chi-square test – Kranzler, Ch. 13.

·
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 – Kranzler, Ch. 11.

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
– Kranzler, Ch. 12.

__EXAM 2__: Monday, November 16

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

·
Measures for
interval data: Pearson’s r and the slope
of the regression line

Kranzler, Ch. 8. Lewis-Beck, pp. 9-25, 43-47.

·
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__: Monday, December 7,