Last Updated: September 21, 2014

This review is
intended to give you a general idea of what may appear on the exam. The exam will cover material from the
assigned readings and material that was presented in the lecture.

**Week1**

A brief overview of the overall research process in political science

Specifying research questions

Literature review

SPSS

Two windows (Data view, variable
view)

Variables

Data entry

Variable labels and value labels

Frequency

**Week 2 **

Quantitative
and qualitative studies

Theory
and data

Improving
research questions

1. A research project should pose a question that is “important” in the
real world

2. A research project should make a
specific contribution to an identifiable scholarly literature

Babbie Ch3

Ethical Issues in
Social Research

Informed consent, confidentiality, anonymity,
etc

Stats: Frequency

Manual calculation

SPSS

**Week 3**

Validity and
reliability

Units of analysis

Individual data, aggregate data

Ecological fallacy (Handout)

Concepts

Operationalization

Multidimensionality

Measurement error

Systematic and random

SPSS

Recoding

**Week 4**

Levels of measurement

Nominal, Ordinal,
Interval

Deductive and inductive

Theory and hypotheses

Variables

Dependent, independent, intervening,
antecedent

Duverger’s law

Democratic peace: Democracies do not go to war with one another. (Economic interdependence, democratic value, citizens' control)

The median voter theorem

Prisoner’s dilemma

Rational choice,
dominant strategy, equilibrium, collective action problem

Criteria for causality

Correlation, time order,
nonspurious

Characteristics of good hypotheses

Descriptive stats

Frequency, Bar chart

Central tendency

Mean,
median, mode (manual calculation)

Dispersion

Range,
variance, standard deviation (manual calculation)

Positive and negative
skew

SPSS

Frequency, central
tendency, dispersion

Excel

Standard deviation

**Week 5**

Isolating the impact of main independent variable

Experimental studies

Experimental
and control groups

Premasurement and post-measurement

Random
assignment

Laboratory and
field experiments

Internal validity
and external validity

Observational Studies

Natural experiments and controlled comparison

Sampling

Random sampling, haphazard sampling (non-random sampling)

Sample size

Confidence level, Accuracy (margin of error), Variability

Sample 1- Male 50%, Female 50% --> High variation

Sample 2- Male 100%, Female 0% --> Low variation

High variation requires a larger sample.

The formula for
standard deviation will be provided.