Soc 2155 Study Guide - University of Minnesota Duluth



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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