Overall Research Terms
 unit of analysis
 scientific method
 inductive vs. deductive
 null hypothesis and research hypothesis
 falsification
 replication
 validity (both internal and external)
 reliability
 generalization (and the distinction between statistical and analytical generalization)
U.S. Census and Census Geography
 the "old" metropolitan geography: MSA, PMSA, CMSA
 the "new" metropolitan geography: metropolitan and micropolitan areas
 Census tracts vs. blocks
 race versus ethnicity variables
 Census regions and divisions
Data Presentation:
 principles of data presentation: basic do's and don'ts of graphs and
tables
 advantages and disadvantages of different types of graphs (bar, column,
scatterplot, pie, etc.)
 ways that graphs distort data
Multiple Regression Analysis
 know how to interpret a multiple regression output (e.g., t score,
F score, Rsquared, adjusted R squared, coefficient, constant, beta,
significance, standard error)
 the mathematical relationship between Total Sum of Squares, Regression Sum of Squares, F, RSquare, etc.
 how to write an equation from the coefficients and use this to make
an estimate
 know the basic assumptions of a regression model (see LewisBeck,
p. 26  )
 homoscedasticity vs. heteroscedasticity
 multicollinearity
 dummy variables
 outliers
Evaluation Research
 program theory
 counterfactual (and compare approaches and pros/cons of each, e.g., beforeafter, random assignment, natural experiments; matchedpairs; regression)
 random assignment
 control vs. experimental group
 rival explanation
 sideeffects (unintended consequences)
 placebo effect
 how regression analysis might be used in evaluation research
Case Study Research
 statistical generalization vs. analytical generalization
 single vs. multiple case studies
 literal replication vs. theoretical replication
 typical vs. exceptional cases
 cases as quasiexperiments
Economic Analysis
 economic base model (multipliers)
 location quotients
 GINI coefficients (and the Lorenz curve)
 costbenefit analysis
 shiftshare analysis

Basic Statistics terms (largely
covered in UP503):
 descriptive vs. inferential statistics (can you explain the difference?)
 univariate, bivariate, multivariate
 levels of measurement: nominal, ordinal and interval
 mean, median, mode
 correlation coefficient
 degrees of freedom
 confidence interval
 normal curve
 statistical significance
 distribution of sample means
 t score
 F score
 difference of means test
 difference of proportions test
 ANOVA  Analysis of Variance
 chisquare
 the difference between a onetail and twotailed test (and when to use one or the other) see Trochim's useful guide
 longitudinal vs. crosssectional data
 panel vs. nonpanel data
 standard error versus standard deviation
 primary vs. secondary data
Relationships between variables:
 ecological fallacy
 spurious relationships
 intervening variables
 correlation vs. causation
 scatterplots (xy plots)
 linear vs. nonlinear relationships
 measurement of the strength of a relationship (r) versus the statistical significance of a relationship (tscore and corresponding probvalue)
 symmetrical vs. non symmetrical relationships
 dependent vs. independent variables
Survey Research:
 sampling terminology: population, sampling frame, sampling element,
sample, sample size, response rate, nonresponses
 probabilistic and nonprobabilistic sampling
 types of sampling: simple random, systematic random, stratified,
clustered, etc.  how they are done; assumptions of each;
advantages and disadvantages of each.
 use of weights to adjust for nonproportional sampling (e.g., with
stratified sampling)
 sampling fraction
 measures and concepts
 questionnaire design: do's and don'ts of wording, ordering,
filtering, open vs. closedended questions, etc.
Demography
 fertility, mortality, migration (components of change)
 cohort survival analysis
 agespecific data (e.g., agespecific fertility)
 fertility rates
 "replacement level" (for fertility rates)
 life expectancy (e_{0})
 components of life
tables (q_{x}
, l_{x}
, d_{x}
, L_{x}
, T_{x}
, e_{x}
)
and basic equations, e.g., q_{x} = d_{x}/ l_{x}; e_{x} = T_{x}/ l_{x}
 population forecasting
 age pyramids
 net vs. gross migration
 types of growth functions (e.g., linear, compounded, exponential)
