Waiver Exam Information                    

The waiver exam is intended for graduate level students
who have taken a course similar to 465 at another University
and wish to have the course count toward their M.A. or M.S. 
degree here at CSU Fullerton.  Additional information on whether
you qualify for the exam are available from Kay Karlson.
                    

The waiver exam is an open-book and open-note exam.  Overall, there
are 200 total points on the exam.  Passing on the exam will be 70% 
or higher.  We provide 2-hours to complete the waiver exam.  Some 
review materials are provided below to help you prepare.  The waiver
exam will be given prior to each semester at an assigned time and date.
Again, contact Kay Karlson for more information.
                    
                    
Items you should know:

Probability
 Know how to recognize
 - conditional p(A|B)
 - permutations (ordering)
 - combinations 
 - significance testing and the binomial  
   distribution

Chi-Square
 - one-dimensional tables (goodness of fit)
 - 2x2 contingency tables
 - what chi-square measures
 - continuity corrections
 - larger contingency tables
 - types of data used in such tables
 - assumptions of chi-square
 - significance testing
 - further analyses with complex tables 

t-tests
 - one-sample t-test (compared to
   population)
 - t-test for independent samples
 - assumptions of t-test
 - homogeneity of variance assumption
 - separate variance estimation formula
 - standard error of the mean
 - unequal sample sizes
 - significance testing

Correlation
 - r formula
 - assumptions
 - % variance accounted for
 - range restrictions
 - significance testing

ANOVA
 - assumptions
 - One-way ANOVA
 - Two-way ANOVA
 - Three-way ANOVA (interp only)
 - summary table components
 - significance testing
 - pros/cons omnibus F test
 - df calculation
 - eta square
 - family-wise error & fw formula
 - multiple comparison procedures
     - a priori
          - t-tests
          - contrasts (orthogonal)
          - modified Bonferonni test
     - post-hoc
          - Fishers LSD
          - Newman-Keuls
          - Tukey
          - Scheffe
 - simple effects testing
     - post-hoc adjustments for Scheffe
 - factorial cells
 - structural model for one-way & two-way   
   designs
 - interpreting interactions
 - condition effect
 - random vs. fixed effects

Repeated measures designs
 - when to use
 - assumptions (including compoind symmetry)
 - one repeated variable
 - mixed designs
 - summary table components
 - correlated t-test used for post-hoc evals
 - interpreting summary table components
 - comparisons to differences scores

Graphs
 - graphing interaction terms, main effects
 - scatterplots
 - simple histograms
 - bar charts
 - Venn diagrams for % variance

Multiple Regression
  - when to use
  - assumptions
  - dummy coding, when to use
  - standard method and stepwise methods
  - testing r-square and r-square change
  - testing the linear model
  - standardized and unstandardized                
       regression coefficients
  - semi-partial regression coefficients
  - importance of predictors
  - suppression effect
  - interpretation of findings
  - interpreting SPSS output
  - Venn diagrams

Trend Analysis
 - when to use
 - linear, quadratic, cubic, quartic line fits
 - orthogonal contrasts
 - powered vectors, their utility
 
Distribution Free Tests
 - advantages, disadvantages
 - utility, when to use
 - Runs test (when to use, calcs)
 - Sign test (when to use, calcs)


Note:
There will probably be SPSS output to
interpret on the Waiver.  You may be provided
with example output from a multiple
regression run focusing on either MR issues
or on Trend Analysis issues.