1. PPA 501 Analytical Methods in Administration Lecture 2a – The Research Process and Developing Research Questions

2. Eight Steps in the Research Process Identify the research problem. Establish research objectives. Decide research strategy. Prepare a research plan. Conduct a literature review. Gather the data. Analyze and interpret the data. Prepare and present the findings.

3. Identify the Research Problem Identify the problem clearly and succinctly. Tips. Pick a topic that interests you. Be sure the topic is not too large to get a handle on within the allotted time and resources. Be sure that the topic is not too narrow that you will not find sufficient information. Try stating your research question as a question: “What effect does the home production of methamphetamine in Thurston County have on the health of children less than twelve years of age living in the same residence?” “What effect do the scope of a disaster, the population and growth of the state, the poverty and ethnic distribution of the state, the economic vulnerability of the state’s infrastructure, and the political dynamics of the disaster have on a president’s decision to grant or not grant a major disaster?”

4. Establish Research Objectives Make clear what each step of the research is to accomplish. This will vary depending on the research question and its underlying theory.

5. Decide on a Research Strategy Choose the strategy that provides the most cost-effective way of gathering the information, and the strategy that produces the best possible answer to the research question. Three broad classes of research strategies. Qualitative Quantitative Combined

6. Prepare a Research Plan An effective research plan (or design) requires decisions on Data sources; Research approaches; Data-gathering instruments; Sampling plan; and Methods of contacting study subjects. Your plan should include a timeline for completion of each stage.

7. Conduct a Literature Review An analysis of prior research on the topic. Involves reading and analyzing published material in books, professional and academic journals, government documents, and other sources. The focus should be the key ideas that may function as leads for further investigation. Are there other ways of looking at the problem that you may have missed?

8. Gather the Data Types of collection Participating in a social situation and recording the findings; Passively observing subjects; Interviewing subjects one at a time or in groups; Preparing a questionnaire to survey a sample; Recording discussions of panelists in a focus group session; Recording the self-administered responses of a panel of subjects; or Reviewing documents, artifacts, or other information sources. Types of sources Primary data collection – collected by researcher. Secondary data collection – collected by others and used by researcher.

9. Analyze and Interpret the Data Establish order to the data and determine its meaning or implications. Must be related to the original study question and research objectives.

10. Analyze and Interpret the Data What researchers want to know: Typical responses; Variation in responses; Distribution of responses; and Relationship among variables. Quantitative responses Frequency distributions. Univariate descriptive statistics. Bivariate statistics. Qualitative responses. Narrative text.

11. Prepare and Present Research Findings An outline of the research report followings the same outline developed during the planning process. Some sections may be completed earlier in the research process. Doing good research: Using good scientific methods to select the sample, gather data, and tabulate the results. Use writing that is clear, concise, and readable. Key problem on style: different disciplines frequently have varying standards.

12. Asking Empirical Questions Research and analysis conjure up images of tedious arguments about remote problems. However, all of us analyze political and administrative events, often ones that effect us directly. Questions and research designs differ, but all ask empirical questions, meaning that the questions can be answered by empirical data, by observations about the world around us.

13. Asking Empirical Questions Empirical versus normative questions Empirical questions – observations about the world around us. Normative questions – normative or value judgments. Normative questions elicit normative statements, value judgments or preferences that contain or imply words such as ought or should, bad or good. Nevertheless, empirical questions can be used to answer normative questions.

14. Describing and Explaining General Patterns Empirical political questions ask for a description; that is, they ask us to describe general patterns and tendencies. They often go one step further and ask about the reasons or explanations for the patterns.

15. Describing and Explaining General Patterns From Descriptions to Explanations Descriptions tell us what is happening. When we collect information about the phenomenon under investigation we are engaging in observation. We attempt to build on the descriptions to try to explain why an event or pattern occurs. Our explanations are usually general rather than specific to an individual. One way to move from description to explanation is to classify the cases or observations we are describing.

16. Describing and Explaining General Patterns Example – IAEM Survey, 2006, Years of Emergency Management Experience

17. Describing and Explaining General Patterns Classify by years of experience Classification can serve as both description and explanation. Do less experienced emergency managers voice more support for DHS responsibility for disasters?

18. Describing and Explaining General Patterns Classify by type of organization worked for. Does organization tell us anything about approving DHS as the appropriate handler for catastrophic disasters?

19. Describing and Explaining General Patterns From Explanations to Theory-Building Intriguing observations lead to research questions. Ideally, you will go one step further by linking your questions and searching for answers in the ongoing process of theory building. A theory assumes that events are not entirely random; it states a general and logical explanation for behavior and events. It forces us to go beyond unique cases and to look for trends and relationships that apply more generally.

20. Describing and Explaining General Patterns Deciding how many cases to look at. Advantages and disadvantages of comparisons across cases versus a single case study. What are they?

21. Three Strategies for Answering Research Questions Historical Narratives Comparative Research Hypothesis Testing

22. Hypothesis Generation Stating and Evaluating Tentative Explanations Usually states a relationship between two or more things Is stated affirmatively (not as a question). Can be tested with empirical evidence. Most useful when it makes a comparison. States how two or more things are related (direction) The theory or underlying logic of the relationship makes sense.

23. Hypothesis Generation Hypothesis examples: Poor: Local governments are having financial difficulties Better: Governments in older urban areas are experiencing more financial hardship than those in recently developed areas. Poor: Race has an influence on elections Better: Minorities are more apt to vote for Democratic candidates than for Republican candidates.

24. Hypothesis Generation Explaining variation in phenomena The phenomenon to be explained is usually referred to as the Dependent Variable.

25. Hypothesis Generation Dependent variable (contd.) Variables – Any measurement of a phenomenon that can vary from observation to observation. For example, gender, age, income, organizational culture. Values – The different conditions or states that each variable can achieve from observation to observation. Cases – The different observations across which a variable varies. Why cases have different values on the dependent variable is what we trying to explain.

26. Hypothesis Generation Using independent variables to explain relationships We can explain the dependent variable by relating it to an independent variable. We will test whether different levels or conditions of the independent variable are associated with different levels or conditions of the dependent variable. Relation or association simply means that cases which differ on the independent variable are likely also to differ in systematic ways on the dependent variable.

27. Sources of research questions From our own observations and experiences (induction). From studies and accounts of others (induction). From theories about relationships (deduction). Via logic (deduction).

28. Sources of research questions Induction – Begin with particular observations or cases and generalize from them. Go from the particular to the general Deduction – Begin with a theory and consider what implications that it has; or examine the premises of an argument and see what conclusions logically follow. Go from the general to the specific.

29. Causation Causation – John Stuart Mill The cause must precede the effect in time. The cause and effect have to be related. Other explanations of the cause-effect relationship have to be eliminated Method of agreement – effect will be present when the cause is present. Method of difference – effect will be absent when the cause is absent. Method of concomitant variation – when both of the above relationships are observed, causal inference will be all the stronger since certain other interpretations of the covariation between cause and effect can be ruled out.

30. Causation Threats to the validity of the causal relationship (alternative explanations) History Maturation Statistical regression Selection Experimental mortality Testing Instrumentation

31. Examples Presidential decision-making and disaster management IAEM Emergency Managers Survey CSUB Analysis of Student Learning Outcomes.