Soc 2155 (Summer, 2006)
Soc 2155 (Summer, 2006)
Midterm exam study guide
In general: there will be 50-60 multiple choice questions, several short answer questions, and some SPSS output that you must interpret. Although I have listed the most important concepts, there may be things on the exam that are not represented here.
1. Introduction to Inquiry
• Ways of “knowing things” (upside/downside of each)
• What happens when direct experience clashes with “what we know”
• How is science different from other ways of knowing?
o The causal, probabilistic nature of science
o Common errors in observation and how science helps avoid them
• Philosophy vs. science (premodern, modern, postmodern)
• Doing science
o Normative or philosophical questions versus empirical questions
o A scientific understanding must…
o Variables (language of science) and attributes
▪ Independent vs. dependent variables
• Dialects in social science--Idiographic versus Nomothetic, Induction and Deduction, Qualitative and Quantitative, Pure versus Applied
• Guidelines for evaluating research (e.g., accuracy, authority…)
o Be able to apply to discussion of scholarly journals, books, internet sites
2. Paradigms, theory, and research
• Paradigms (what are they, why important)
o In social science
▪ Early positivism
▪ Conflict
▪ Symbolic interactionism
▪ Structural functionalism
• Can we study society in a “rational and objective manner?”
o Ash experiments, The Sherif “flashlight” study
3. Ethics and Politics
• Define ethics and differentiate from politics
o Milgram experiments, Laud Humphreys study, Tuskegee
o Pillars of the ethics code in social science (voluntary, no harm)
▪ Informed consent
▪ Anonymity and confidentiality
▪ Deception/debriefing
▪ Ethics for analysis and reporting
o Institutional review board (what are they, what do they do, does UMD have one…).
• Politics
o What is ideology?
▪ American political ideologies
o Terms/concepts in ideology
▪ Intersubjectivity
▪ Knowledge destruction
4. Research design
• Three purposes of research (e.g., define, example…)
• Criteria for establishing causation in social science (and how to demonstrate each)
o Common mistakes for interpreting causal relationships
o Necessary and sufficient
• Units of analysis (be able to find this critter in an example)
o Individual vs. group/aggregates
o Mistakes relating to unit of analysis (ecological fallacy/reductionism)
• Time in research
o Cross-sectional vs. longitudinal
▪ Advantages (downsides) of longitudinal research
▪ Types of longitudinal studies
o Ways to get around doing longitudinal research (and problems with these)
5. Conceptualization, Operationalization
• Concepts that social scientists study as “made up”
o But—can still measure (agreement)
• The process of conceptualization
• The danger of “reification”
• Kaplan’s 3 classes of things that scientists measure (observables)
• Indicators (define, example)
o Dimensions (example)
• Real, nominal, operational definitions
• Why definitions (operational) are more problematic for descriptive than for explanatory studies
• Operationalization (decision making)
o Range of variation
o Qualities of variables (mutually exclusive, exhaustive)
o Levels of measurement (nominal, ordinal, interval, ratio)
o Multiple indicators
• Reliability and validity (define, explain, examples)
o Tension between these two concepts
o How to check/demonstrate reliability and validity
6. Indexes and Scales
• Why use a composite measure?
• Similarity and differences between an index/scale
• Constructing a scale
o Items should be empirically related (but not measure exactly the same thing)
o Unidimensionality
o Variance
o Missing data (and solutions)
• Scaling
o Bogardus scale
• Be able to interpret SPSS output regarding an index
7. Sampling
• Why sample?
• Probability vs. non-probability samples
o Advantage and disadvantage of each
o Types of each
• Sampling terminology
o Element, population, sample, sampling frame
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