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SOCIOLOGICAL RESEARCH METHODS
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
THE BASIC WHEEL OF SCIENCE
Theory
Hypothesis
Observation
Conclusion
Deduction
Induction
RESEARCH PROCESS: STAGE 1-ABSTRACT
THOUGHT DEVELOPMENT
Theory
Testing OR
Theory
Development
Idea
General
Question
INDUCTIVE INQUIRY
Question
About Social
Reality
Observation
Concept Concept
THEORY
DEDUCTIVE INQUIRY
Question
About Social
Reality
Concept Concept
THEORY
HYPOTHESIS
Independent Variable (X) Dependent Variable (Y)
Intervening Variable (Z)
THEORIES AND HYPOTHESES
 Theory
 Statement explaining the relationship between
phenomena of interest
 Hypothesis
 Testable expectation about the relationship between
phenomena of interest
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
EXAMPLES OF COMMON VARIABLES IN
SOCIOLOGICAL RESEARCH
 Demographic Characteristics
 Race/ethnicity
 Gender
 Socioeconomic Status
 Income/Assets
 Education
 Other Variables
 Perceived Discrimination
 Social Isolation
RESEARCH PROCESS: STAGE 2-PLANNING
Research Method
Specify
Concepts/Variables
Operationalization
Population/Sample
COMMON RESEARCH TOOLS
 Surveys
 Face-to-Face
 Mail
 Telephone
 Internet
 Qualitative Field Research
 In-Depth Interviews
 Ethnography
 Participant Observation
ADDITIONAL RESEARCH TOOLS
 Content Analysis
 Experiments
 Historical Research
 Evaluation Research
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
RESEARCH PROCESS: STAGE 3-DATA
COLLECTION, ANALYSIS, AND DISSEMINATION
Data
Collection
Data
Processing
Analysis Reporting
GATHERING DATA
 Establish Population of Interest
 Primary vs. Secondary Data
 Sampling technique (primary data collection)
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
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
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
QUALITATIVE DATA PROCESSING/ ANALYSES
 Transcription
 Coding and Memoing
 Finding Patterns in the Data
 Summarizing
STATISTICAL ANALYSES
 Statistic
 Numerical summary of a sample
 Parameter
 Numerical summary of a population
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?
STATISTICAL ANALYSES (CONT.)
 Univariate Statistics
 Percentage and Rates
 Averages
 Multivariate Statistics
 Correlation
 Regression Models
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
RELIABLE, BUT NOT VALID
RELIABLE AND VALID
NOT RELIABLE, NOT VALID
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
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
RESEARCH ETHICS
 Institutional Review Board (IRB) approval
 Informed Consent
 Debriefing after experiments
 DO NO HARM TO PARTICIPANTS/SUBJECTS!

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Sociological research

  • 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
  • 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
  • 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!