Sociology 4 Midterm Study Guide

Unit I. Approaches to Social Research (Course preview)

Four principal research strategies (experiments, surveys, field and observational research ,
and use of available data) 1

concepts and measures (operational definitions)

measurement reliability and validity 2

independent variable, dependent variable 3

The interplay of theory and research

deduction and induction (wheel of science) 4

Evidence supporting causality (criteria) 5 10

1. association

2. direction of influence

3. eliminate rival explanations (control procedures)

Logic of Experimentation

manipulated independent variable (treatment)

random assignment

test of statistical significance

internal and external validity

Reading research reports

units of analysis 6

aggregate data

ecological fallacy 7

time frame

cross-sectional design 9

longitudinal design

trend study

panel study 8

cohort study

birth cohorts (age, period, cohort effects)

Reading tables

positive and negative (inverse) relationships

statistical significance

percentaging and reading tables

multivariate analysis

logic (let one independent variable vary at a time, while controlling the others)

partial regression coefficients (slopes) 11

dummy variables (binary, dichotomous)

Unit II. From Concepts to Measures

Operational definitions (manipulation operations, measurement operations)

sources of variation: true values, systematic error (bias), random error 12

coding responses to open-ended questions 13

Levels of measurement

Nominal 15

mutually exclusive, collectively exhaustive 14

ordinal

interval

ratio

Reliability assessment: 16

stability measures (test-retest)

equivalence measures (split-half/internal consistency, intercoder reliability)

Validity assessment:

1. subjective (content, face) 17

2. criterion-related 18

3. construct

a. correlations with related variables
b. convergent validity
c. discriminant validity
d. known groups

Unit III. Generalizability of Findings

Reasons for probability sampling (reduced cost, greater speed, better quality, greater flexibility, unbiased selection, efficient investment of resources)

Initial steps

1. define target population of interest 19

2. construct sampling frame (list, rule) 20

Review of statistical inference (population, sample, and sampling distribution) 

parameter, statistic 21

standard error (factors affecting sampling error) 22

nonsampling errors in surveys (incomplete sampling frame, incomplete data collection, response errors)

Probability sampling designs

simple random sampling (SRS)

systematic sampling

stratified sampling

cluster sampling 25

area sampling

Nonprobability designs 

convenience sampling

purposive or judgmental sampling 23

quota sampling 24

snowball sampling