Soc 2155 Study Guide
Soc 2155 Study Guide
Fall, 2009
Chapter 10 – Qualitative Field Research (QFR)
• Within this area, the issue of validity versus reliability
• History of QFR in sociology
• Terms like “reactivity,” “going native,”
• Ethical issues in field research
• Issues (problems) in dealing with subjects
• The scientific benefit and downside of being a complete participant in a group or process one is trying to research.
• The research paradigms (be able to recognize examples on a multiple choice)
o Naturalism
o Ethnography
o Ethno methodology
o Grounded theory
o Case Study/Extended Case Method
o Institutional Ethnography
o Participatory Action Research
• Focus groups
o What are they, how useful, limitations, etc.
Chapter 11 – Unobtrusive Research
• Content Analysis (what is it, where appropriate, etc)
o Latent vs. manifest coding
o Strengths and weaknesses
• Existing stats (what is it, where appropriate, etc)
o Ecological fallacy (again)
o Durkheim’s stuff
o Validity problems (UCR data)
• Comparative/Historical (what is it, where appropriate, etc)
o Examples (know) = Marx, Weber
o Sources of data
o Analytical techniques (ideal types)
Chapter 12 – Evaluation Research
• Describes purpose of research not method
o Types of evaluation research (e.g., cost/benefit, program, social indicators…)
• Why more popular of late
• Why are outcome evaluations (see, Scared Straight) often ignored?
• Experimental designs (review)
o Time series (problems with this design), multiple time series
o Quasi-experimental
• Qualitative (e.g., low birth-weight study) evaluation
• Process vs. Outcome evaluation
• Response variable
• The value of cost/benefit analyses, even where the response variable (e.g., crime) is not easily measured in dollars.
Chapter 13 – Qualitative Data Analysis
o Cross-case
o variable-oriented vs. case oriented
o Constant-comparison method
o Semiotics (ad research)
o Conversation analysis
o Concept mapping
Chapter 14 – Quantitative Data Analysis
• Inferential stats (what are they, why do researchers calculate)
o E.g., making an “inference” about the population based on your sample
o Example we used was chi-squared
• Measures of strength (what are they)
o Cramer’s V as our example
• Be able to interpret the following in an SPSS printout of a cross tabs
o Chi-square
o Sig value
o The percent differences to describe a relationship
o Cramer’s V
Of course, things like “level of measurement” and other big points from the class (null vs. research hypothesis, independent/dependent variable) remain fair game.
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