Sociological research

1. Sociological Research Methods

2. Research Methods Research Methods Approaches to inquiry Used to describe, explore , and explain social reality Quantitative Methods Used to collect numerical information or information that can be converted into numerical data Qualitative Methods Used to collect information that is not readily convertible into numerical data

3. The Basic Wheel of Science Deduction Induction

4. Research Process : Stage 1-Abstract Thought Development

5. Inductive Inquiry Question About Social Reality Observation Concept Concept THEORY

6. Deductive Inquiry Question About Social Reality Concept Concept THEORY HYPOTHESIS Independent Variable (X) Dependent Variable (Y) Intervening Variable (Z )

7. Theories and Hypotheses Theory Statement explaining the relationship between phenomena of interest Hypothesis Testable expectation about the relationship between phenomena of interest

8. Concepts and Variables Concepts Imprecise mental abstractions of phenomena Concepts are the building block of theories ( Babbie 2013) Variables Concepts comprised of at least two measurable categories

9. Examples of Common Variables in Sociological Research Demographic Characteristics Race/ethnicity Gender Socioeconomic Status Income/Assets Education Other Variables Perceived Discrimination Social Isolation

10. Research Process : Stage 2-Planning

11. Common Research Tools Surveys Face-to-Face Mail Telephone Internet Qualitative Field Research In-Depth Interviews Ethnography Participant Observation

12. Additional Research Tools Content Analysis Experiments Historical Research Evaluation Research

13. Operationalization Operationalization Operationalization is the process where we specify how we will measure concepts of interest unambiguously Example of operationalization We will measure education with four mutually exclusive categories Less than high school High school graduate / GED Some college College graduate or higher

14. Research Process : Stage 3-Data Collection, Analysis, and Dissemination

15. Gathering Data Establish Population of Interest Primary vs. Secondary Data Sampling technique (primary data collection)

16. Populations and Samples Population Entire collection of units of interest E.g., All adults in the United States Sample A subset of units from our population of interest E.g., 2,000 adults in the United States

17. Sampling Techniques: Nonrandom Sampling Nonrandom Sampling Can be used naively to get an easy sample U sed more appropriately in qualitative research Provides one with good informants More attention on detailed data than generalizable data

18. Sampling Techniques: Random Sampling Random Sampling Random means that samples are selected according to chance, not personal judgment Generally used in quantitative research Intended to provide a representative sample

19. Qualitative Data Processing / Analyses Transcription Coding and Memoing Finding Patterns in the Data Summarizing

20. Statistical Analyses Statistic Numerical summary of a sample Parameter Numerical summary of a population

21. Statistical Analyses (cont.) Descriptive Statistical Analyses A nalyses used to describe your sample E.g., what is the average income in your sample of 2,000 adults in the United States? Inferential Statistical Analyses Analyses that uses information from the sample to make estimates about the population of interest E.g., based on the sample data, what is the estimated average income of all adults in the United States?

22. Statistical Analyses (Cont.) Univariate Statistics Percentage and Rates Averages Multivariate Statistics Correlation Regression Models

23. Reliability and Validity Reliability -Degree to which an instrument or test yields similar results on repeated trials R eliability pertains to the consistency of results Tells us that we are measuring something—not necessarily what we want though Validity -Degree to which an instrument or test actually measures what we intend to measure

24. Reliable, but not valid

25. Reliable AND Valid

26. Not Reliable, Not Valid

27. Hypothesis Testing Null Hypothesis -default position; assumed to be true until proven otherwise Null hypothesis typically specifies that there is no relationship between 2 or more phenomena Alternative Hypothesis -The hypothesis for which we are trying to find support Hypotheses are falsifiable , but never proven

28. 3 Criteria for Causality Correlation 2 variables must be related in some way Time-Order The causal mechanism must precede the effect in time Non-Spuriousness Relationship between 2 variables cannot be explained by some third variable

29. Research Ethics Institutional Review Board (IRB ) approval Informed Consent Debriefing after experiments DO NO HARM TO PARTICIPANTS/SUBJECTS!