Introduction to Political Science Research Methods

1. Research Methods Introduction

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 • Formulation of Theory • Operationalization of Theory • Selection of Appropriate Research Techniques • Observation of Behavior (Data Collection) • Analysis of Data • 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: • 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 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. Inductive Reasoning

13. 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. Deductive Reasoning

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