1. PPA 415 – Research Methods in Public Administration Lecture 1 – Research Design

2. Language of Research Key terms. Theoretical – developing, testing, or exploring the ideas that social researchers have about the way the world operates. Empirical – based on observations and measurements of reality. Nomothetic – pertains to the general case rather than the individual.

3. Language of Research Key terms (contd.) Idiographic – focused on the individual rather than the general case. Probabilistic – most social science relationships are based on tendencies or probabilities. Causal – focused on cause-effect relationships to develop the capacity to predict or shape the world.

4. Types of Research Questions Descriptive – Designed to describe what is going on or what exists. Relational – Designed to look at the relationship between one more variables. Causal – Designed to determine whether one or more variables causes or effects one or more outcome variables. Research questions are cumulative.

5. Time Relationships Cross-sectional – Measurements made at one point in time. Longitudinal. Repeated measures – two or three points in time. Time series – multiple points in time.

6. Types of Relationships Correlational – Establishes relationships between two or more variables. Causal – Establishes that one or more variables causes or determines or more outcome variables. Spurious – The difference between correlational and causal depends on the influence of third variables.

7. Variables Variables are measurements that take different values for different cases. Attribute – each value of a variable is known as an attribute, e.g., the variable gender has two attributes, male and female. When examining the relationship between variables, the causal variable that influences is called the independent variable; the effect variables that is influenced is called the dependent variable. The attributes of the variable must be exhaustive and mutually exclusive.

8. Hypothesis A hypothesis states an explicit relationship between an independent and dependent variable: e.g., as levels of participation increase, voting turnout increases. Alternative or research hypothesis: X causes Y. Null hypothesis: X and Y have no relationship. In research, you test the probability of no relationship or no effect.

9. Type of data Qualitative – measured with labels or categories. Quantitative – measured with numbers. The distinction is usually academic.

10. Unit of Analysis Depends on the research question. Individuals. Groups. Artifacts. Geographical units.

11. Research Fallacies Ecological fallacy. Drawing conclusions about individuals on the basis of groups or aggregations. Exception fallacy. Making generalizations about groups or aggregations on the basis of individuals.

12. Research Process Begin with broad questions. Narrow down, focus in. Operationalize. Observe. Analyze data. Reach conclusions. Generalize back to questions.

13. Research Stages Research problem. Research question. Program (cause). Units. Outcomes (effect). Design.

14. Validity Model

15. Types of Validity Type of ValidityConclusionProcedure ConclusionRelationshipAnalysis InternalCausalDesign ConstructMeasurement ExternalGeneralizabilitySampling

16. Statistics Descriptive – (1) when the researcher needs to summarize or describe the distribution of a single variable (data reduction) and (2) when the researcher wishes to understand the relationship between two or more variables (association). Inferential – when the researcher wants to generalize findings from a sample to a population.

17. Variables Discrete – a variable is discrete variable if it has a basic unit of measurement than cannot be subdivided. Continuous – a variable is continuous if the measurement of it can be subdivided infinitely.

18. Levels of Measurement Nominal level of measurement – Places cases in categories Ordinal level of measurement – Places categories in order of more or less. Interval level of measurement – Uses a unit of measurement. Ratio level of measurement – Has a substantive zero point.

19. Edward Tufte’s Principles of Quantitative Reasoning Documenting the sources and characteristics of the data. Insistently enforcing appropriate comparisons. Demonstrating mechanisms of cause and effect.

20. Edward Tufte’s Principles of Quantitative Reasoning Expressing those mechanisms quantitatively. Recognizing the inherently multivariate nature of analytic problems. Inspecting and evaluating alternative explanations.