**POLS=20
641**

**Introductory=20
Analysis of Political Data**

**Fall=20
2010**

**Professor=20
Mikel Wyckoff**

**Zulauf=20
425 753-7039 mwyckoff@niu.edu **

**Office=20
Hours: M =
**

** & by=20
appointment**

This=20
course provides an introduction to basic statistical methods frequently=20
encountered in the social sciences. =20
Topics we will cover include: (1) descriptive statistics (for =
example,=20
means and standard deviations); (2) statistical inference (random =
sampling and=20
hypothesis testing with the aid of statistical significance tests); and =
(3)=20
measures of relationship and association. =20
Students will also get an introduction to =

Although=20
I personally enjoy statistical methods very much, I suspect that at =
least some=20
of you approach this class a bit grudgingly and with a certain amount of =
anxiety. Let me assure =
everyone=20
that the course is not *that* =
difficult=20
(almost everyone who is willing to put in the time and effort can expect =
to earn=20
a respectable grade). Let =
me=20
suggest, furthermore, that if you give the material a fair chance it is =
likely=20
that you will find these research tools useful (at the very least) and =
indeed,=20
interesting. For those =
experiencing=20
genuine fear and anxiety, the textbook's section on =93Overcoming Math =
Anxiety=94=20
may be helpful.

**REQUIRED=20
**

The=20
following books are required and should be available at local =
bookstores. If not, they are readily =
available from=20
online sources. =20

=B7 =20
John=20
H. Kranzler, *Statistics for the =
Terrified*, Prentice Hall, 4^{th} ed., 2007. =

=B7 =20
Michael=20
S. Lewis-Beck,=20
*Applied Regression: An =
Introduction*,=20
Sage University Paper #22.

Additional=20
required readings, in the form of handouts or readings that can be =
located=20
online, also will be assigned.

**OTHER=20
POTENTIALLY USEFUL **

In=20
this course we will spend a certain amount of time computing statistics =
by hand,=20
but we will primarily make use a statistical software package called=20

=B7 =20
Philip=20
H. Pollock III, *An SPSS =
Companion to=20
Political Analysis*, CQ Press, 2008.

=B7 =20
Marija=20
Norusis, *SPSS**=20
16.0 Guide to Data Analysis,=20
2/E, Prentice Hall, 2009.*

=20

**OTHER=20
REQUIREMENTS**

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

__Computer=20
Exercises__. The remaining 30% of your =
grade will be=20
determined by your performance on computer assignments which will =
require the=20
use of

__Take-Home=20
Problems__. Throughout the semester I will =
assign=20
sets of problems for you to work outside of class. I expect you to do these =
problems, and=20
we will spend a good deal of time on them in class, but I will not =
collect them=20
and grade them. Similar=20
computational problems will appear on the midterm and final exams, so =
devoting=20
significant time to the take-home problems is well justified despite the =
fact=20
that they will not be graded.

**COURSE=20
OUTLINE AND READING ASSIGNMENTS**

**I. PART ONE: Descriptive=20
Statistics**

=B7 =20
Introduction=20
and basic math review =96 Kranzler, Appendix A and Ch. 1-2. =

=B7 =20
Introduction=20
to

Do the =
introduction and perhaps skim some of the other topics in the =
tutorial.

=B7 =20
Variables,=20
Levels of Measurement, Frequency Distributions =96 =

=B7 =20
Measures=20
of Central Tendency and Variation =96

=20

=B7 =20
The=20
Normal Distribution =96

=B7 =20
Percentiles=20
and Standardized Scores =96 Kranzler, Ch. 7, pp. 71-77 and 80-86.

__EXAM=20
I__**: **Monday,=20
September 27

**II. PART TWO: Data Analysis =96 Using =
Independent=20
Variables To Explain Dependent Variables**

**A. Analyzing Categorical Data =
with=20
Crosstabs**

1. Introduction to crosstabs; =
relationships=20
and measures of association =20

=B7 =20
The=20
Crosstabs Procedure =96 see =93How to Read a Crosstabulation=94=20
(handout).

=20

=B7 =20
Hypothesis=20
Testing I: The chi-square =
test =96=20
see =93The Chi-Square Test of Significance=94 (handout).

=B7 =20
Measures=20
of association for nominal and ordinal Data. =96 See =93Measures of =
Association,=94=20
pp. 144-151 for now (handout).

=B7 =20
Holding=20
=93third=94 variables constant using crosstabs =96 Additional reading=20
TBA.

2. Thinking about inferential =
statistics=20
(How do significance tests and confidence intervals work?)=20

=B7 =20
Random=20
Samples and the need for Inferential Statistics

=B7 =20
The=20
concept of a sampling distribution

=B7 =20
Formal=20
hypothesis testing; type I and II errors =96 =

**B. Analyzing Interval Level =
Dependent=20
Variables and Categorical Independent =
Variables**

1. The t-test =96 Analyzing =
differences of=20
means observed in two groups

=B7 =20
Additional=20
Thoughts on Sampling Distributions; Standard =
Errors.

=B7 =20
Hypothesis=20
Testing II: The t-test =
=96 Kranzler,=20
Ch. 11. =

2. ANOVA (Analysis of Variance) =
=96 Analyzing=20
differences of means observed in three or more =
groups

=B7 =20
Hypothesis=20
Testing III: The F-test =
and=20
Analysis of Variance =96 Kranzler, Ch. 12. =20

__EXAM=20
2__: Monday, November =
8

**C. Analyzing Two or More =
Continuous=20
Variables =96 Bivariate and Multivariate Regression=20
Analysis**

=B7 =20
Measures=20
for interval data: =
Pearson=92s r and=20
the slope of the regression line

=20
Kranzler, Ch. 8. Lewis-Beck, pp. 9-25,=20
43-47.

=B7 =20
Significance=20
tests and confidence intervals =96 Lewis-Beck, pp. =
30-37.

=B7 =20
Multivariate=20
analysis =96 Lewis-Beck, pp. 47-58.

=B7 =20
Dummy=20
variable analysis =96 Lewis-Beck, pp. 66-71.

__EXAM 3__: Monday, December 6, =