This document provides an introduction to research methods in political science. It discusses the differences between normative and empirical evaluations and outlines principles of scientific inquiry. It then describes the scientific study of politics and the political science research process. This includes formulating theories, operationalizing concepts, collecting and analyzing data, and interpreting results. The document also outlines subfields in political science and different types of research questions. It discusses what constitutes a theory and the components and types of theories. Finally, it explores variables, hypotheses, and relationships between variables that can be investigated through political science research.

1. I N T R O D U C T I O N
Research Methods

2. Scientifically Investigating Phenomenon
 Normative vs. Empirical Evaluations
 Normative = questions of value: “what ought to be”
 Empirical = questions of fact: “what is”
 Is there a grey area? How do we determine if it is an ‘ought’
or an ‘is’ question?
 Principles of Scientific Inquiry
 Be open-minded
 Be skeptical
 Be objective
 Be creative
 Be informed

3. Political Science
 The “Science” of “Politics”
 Political Science Methodology
 Process & methods in using empirical research to achieve
scientific knowledge about political phenomena
 Why should we learn about the study of politics?
 Role as a citizen
 Learning to be a scientific researcher
 Why conduct research?
 To accumulate and extend knowledge and understanding of a
phenomena that may be applicable to problems/solutions
relevant to society.
 To satisfy intellectual curiosity

4. Six Stages of the Research Process
1. Formulation of Theory
2. Operationalization of Theory
3. Selection of Appropriate Research Techniques
4. Observation of Behavior (Data Collection)
5. Analysis of Data
6. Interpretation of Results

5. Sub-fields in Political Science
 American Politics
 Comparative Politics
 International Relations
 Public Policy (Public Administration)
 Political Theory
 Political Methodology

6. What is Political Science?
 “Politics is not an exact science.” (Bismarck 1863)
 Politics: art or science?
 The study of politics: art or science?
 How do we know what we know?
 Scientific research / Behavioralism
 Research question
 …and the search for an empirical answer

7. Types of Research Questions
 There are three basic types of questions that research
projects can address:
1.Descriptive.When a study is designed primarily to
describe what is going on or what exists. Public
opinion polls that seek only to describe the
proportion of people who hold various opinions are
primarily descriptive in nature. For instance, if we
want to know what percent of the population would
vote for a Democratic or a Republican in the next
presidential election, we are simply interested in
describing something.

8. Types of Research Questions (con’t)
2. Relational.When a study is designed to look at
the relationships between two or more variables. A
public opinion poll that compares what proportion
of males and females say they would vote for a
Democratic or a Republican candidate in the next
presidential election is essentially studying the
relationship between gender and voting preference.

9. Types of Research Questions (con’t)
3. Causal.When a study is designed to determine
whether one or more variables (e.g., a program or
treatment variable) causes or affects one or more
outcome variables. If we did a public opinion poll
to try to determine whether a recent political
advertising campaign changed voter preferences,
we would essentially be studying whether the
campaign (cause) changed the proportion of voters
who would vote Democratic or Republican (effect).

10. What is Theory?
 “Theories are sets of logically related symbols that
represent what we think happens in the world.” (Manheim,
et al. 2006: 15)
 A theory is “a possible explanation for events, often a set of
logically related assumptions and propositions” (Manheim,
et al. 2006: 415)
 “…theories are no more or less than a priori reasoning
about the relations among variables.” (Bueno de Mesquita
1981: 9)

11. 2 Types of Theoretical Reasoning
 Inductive
 specific to general
 search for uniformity
 Deductive
 general to specific
 logically derived theoretical consequences

12. Inductive Reasoning
Inductive reasoning works
the opposite of deduction
moving from specific
observations to broader
generalizations and
theories.
Informally, we sometimes
call this a "bottom up"
approach (please note that
it's "bottom up" and not
"bottoms up" which is the
kind of thing the
bartender says to
customers when he's
trying to close for the
night!).
In inductive reasoning, we
begin with specific
observations and
measures, begin to detect
patterns and regularities,
formulate some tentative
hypotheses that we can
explore, and finally end up
developing some general
conclusions or theories.

13. Deductive Reasoning
Deductive reasoning
works from the more
general to the more
specific. Sometimes this is
informally called a "top-
down" approach.
We might begin with
thinking up a theory about
our topic of interest.
We then narrow that down
into more specific
hypotheses that we can
test.
We narrow down even
further when we collect
observations to address
the hypotheses.
This ultimately leads us to
be able to test the
hypotheses with specific
data -- a confirmation (or
not) of our original
theories.

14. Both Types Necessary?
 “Because a theory’s usefulness can only be judged
empirically, while an empirical generalization’s
truthfulness can only be judged logically, neither
inductive nor deductive reasoning by itself is
adequate.” (Bueno de Mesquita 1981: 9-10)

15. Characteristics of Useful Theories
 Testable / Falsifiable
 Logically sound / Consistent
 Communicable
 General
 Parsimonious
 Accurate

16. Components of a Theory
 Concepts
 Assumptions
 Variables
 Dependent
 Independent
 Hypotheses
 Relationship between (among) variables
 Direction

17. Types of Variables
 Dependent Variables
 A dependent variable is a variable dependent on another
variable: the independent variable. In simple terms, the
independent variable is said to cause an apparent change in, or
simply affect, the dependent variable
 Independent Variables
 An independent variable is a hypothesized cause or influence
on a dependent variable.
 This might be a variable that you control, like a treatment, or a
variable not under your control, like an exposure. It also might
represent a demographic factor like age or gender.

18. IVs & DVs: An Example
 Example 1
 The wages of an employee depend on the time worked.
Time is the independent variable that varies among
employees, and the wages are calculated directly from
the total time worked. Thus wages are dependent on time
worked.
 In a call centre, the number of customers serviced per
hour, depends on the number of agents, and average
service time per customer. In this case number of
customers is a dependent variable, entirely dependent on
the other two independent variables namely agents, and
average service time.

19. Hypotheses
 A hypothesis is a specific statement of prediction. It
describes in concrete (rather than theoretical) terms
what you expect will happen in your study.
 A deductive research design should include a set of
exhaustive hypotheses: i.e. your predictions should
cover all possible conceivable outcomes related to
your two variables.
 Null Hypothesis
 Research Hypothesis

20. Relationships Between Variables
 Covariational relationship
 When X goes up, Y goes up
 Causal relationship
 X  Y
 Spurious relationship
 a relationship that appears to exist at face value, but that
disappears when you control for another variable.
 Other causal relationships
 Indirect causation: X  Z  Y
 Multiple causation: X  Y; S Y; D  Y
 Intervening variable(s): X  Z  Y

21. Spurious Relationships
 Once a group of students decided to study empirically the causes of
drunkenness.
 They drank vodka and water. Got drunk.
 They drank rum and water. Got drunk.
 They drank scotch and water. Got drunk.
 They drank bourbon and water. Got drunk.
 They drank gin and water. Got drunk.
 They looked at the patterns of their data and saw that water appeared in
every instance in which they got drunk, while no other factor appeared to
remain in every case. They concluded that water made them drunk. Further
research indicated that each of the substances combined with the water
contained alcohol.
 The conclusion that water makes you drunk is spurious. By looking for
other variables and other patterns we find that alcohol is the culprit
variable.

22. Variables
 A characteristic that takes on different values from
one case to another (or, for a given case, from one
time to another)
 Dependent variable
 Independent variable
 Intervening variable
 Antecedent variable
 Control variable (later)

23. Investigating Causality
 Is there covariation?
 Does hypothesized cause precede effect? (causal
order)
 Is there a theoretical relationship between cause and
effect? (causal linkage)
 Can other explanations (simultaneous relationships)
be eliminated? (alternative causality)

24. Logical Relationships
 Necessary conditions
(if x then y)
 Sufficient conditions
(if y then x)
 Necessary and sufficient conditions
(iff x then y)

25. Some Examples
 Free elections, Democracy
 Democracy, US interests
 Democratic states (2+), Peace
 Higher levels of education, Higher levels of political
participation
 Flat (regressive) tax, Fairness