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
Theory
Hypothesis
Observation
Conclusion
Deduction
Induction

4. RESEARCH PROCESS: STAGE 1-ABSTRACT
THOUGHT DEVELOPMENT
Theory
Testing OR
Theory
Development
Idea
General
Question

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
Research Method
Specify
Concepts/Variables
Operationalization
Population/Sample

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
Data
Collection
Data
Processing
Analysis Reporting

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
 Used 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
 Analyses 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
 Reliability 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!