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.