This
review is intended to give you a general idea of what may appear on the
exam. The exam will cover material from
the assigned readings and material that was presented in the lecture.
Please
bring a calculator.
II. Causality (
III. Levels of measurement
Nominal
Ordinal
Interval/Ratio
IV. Descriptive Statistics
V. ANOVA
Manual
calculation (SPSS)
VI. Measures of Association
A. Crosstabs
Know how to produce a cross-tabulation
Know how to read a cross-tabulation (both bivariate and multivariate)
Know how to control for a third variable (Nominal and ordinal variables only)
(SPSS)
B. Tests of statistical significance and measures of association
Know
how to write a hypothesis
Know
how to test a hypothesis
Statistical significance
Strength of association
Direction of association
Substantive interpretation
Bivariate association
Cramer’s V, Tau b, Tau c, Pearson’s r
Controlling for a third variable (Nominal and ordinal variables only)
Cramer’s V, Tau b, Tau c
(SPSS)
VII. Two-variable regression analysis
A. Intercept and slope coefficient (estimation and
interpretation)
B. Population/sample regression function (Diagram
for PRF and SRF)
C. The difference between ui and ui hat and yi
and yi
hat
D. Goodness of Fit
E. Assumptions
F. Calculating ui hat and yi
hat
F. SPSS
VIII. Multiple regression analysis
A. Intercept and slope coefficients (interpretation)
B. Assumptions
C. Testing Hypotheses
Against One-sided and
Two-sided Alternatives, Computing p-values for t Tests
Example
4.3
D. Economic, or Practical, versus Statistical
Significance
E. Confidence Intervals
F. Testing Multiple Linear Restrictions: The F Test
The
R-Squared Form of the F Statistic
G. The F Statistic for Overall Significance of a
Regression
C. SPSS
IX. The following formulae will be provided. The
tables for t and F will also be provided
ANOVA

SIMPLE REGRESSION ANALYSIS
Estimation of SRF

Hypothesis
Testing

GOODNESS OF FIT

LOGARITHMIC FUNCTION

MULTIPLE REGRESSION
Hypothesis
Testing

Confidence
Intervals
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Testing
Multiple Linear Restrictions
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The
F Statistics for Overall Significance of a Regression
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