Statistics and Research Methods

Study Guides for Spring '05

• Study Guide 1
• Study Guide 2
• Final Exam Study Guide

Study Guide for first exam

naturalistic observation
correlation
experimental approach
dependent variable
independent variable
confounding variables
null hypothesis

alternative hypothesis
internal validity
external validity
subject variable
descriptive vs. inferential
sample vs. population
scales of measurement
normal distribution
skewed distribution
mean, median, mode
variance
standard deviation
standard error
z-scores
frequency histogram
rules of probability
random selection
random assignment
Type I and Type II errors
1-tailed and 2-tailed tests
z-test
central limit theorem
power
alpha, beta
t-test
parametric statistics
significant difference
critical value
degrees of freedom
confidence interval
Pearson r correlation
one-way chi square
expected frequency



other things you should be familiar with:

how to interpret SPSS output for:
correlation
1 sample t-test
chi square test


how to use these tables:
z  (table 1)
t   (table 2)
Pearson's r  (table 3)
chi square (table 8)

how to calculate by hand:
z-test
1 sample t-test
confidence intervals
one-way chi square

Study Guide for the second exam

dependent variable
independent variable
confounding variables
null hypothesis
subject variable
sample vs. population
variance
standard deviation
standard error
Type I and Type II errors
1-tailed and 2-tailed tests
power
"alpha, beta"
nonparametric statistics
critical value
degrees of freedom
scales of measurement
p-value
Wilcoxon rank-sum test
between subjects
within subjects
confidence interval
effect size
Mann-Whitney U test
random assignment
random selection
matched-groups
repeated measures
Solomon 4-group design
history
maturation
carry-over effects
mortality
practice effects
ceiling and floor effects
regression to the mean
demand characteristics
double blind
complete counterbalancing
partial counterbalancing
assumptions for all stats
Wilcoxon matched pairs signed-rank
paired (dependent samples) t test

other things you should be familiar with:

when and how to compute:
2-way chi square
independent t-test
dependent t-test
confidence intervals
effect size

how to use tables
how to interpret SPSS output

Study Guide for the final exam

dependent variable
independent variable
confounding variables
null hypothesis
subject variable
sample vs. population
variance
standard deviation
standard error
Type I and Type II errors
1-tailed and 2-tailed tests
power
"alpha, beta"
nonparametric statistics
critical value
degrees of freedom
scales of measurement
p-value
between subjects
within subjects
between-groups variability
within-groups variability
sum of squares
mean square
experiment-wise error rate
grand mean
error variance
Kruskal-Wallis anova
post-hoc analyses
Bonferonni correction
factorial design
residual
mixed design
main effects
interaction effects
partial correlation
quasi-experimental design
subject variables
time-series designs
interrupted time series
reversal design
multiple time-series design
cross-sectional
longitudinal
cohort design
non-equivalent control group
eta squared
confidence intervals
analysis of covariance


other things you should be familiar with:
when and how to conduct:

between-subjects ANOVA
within-subjects ANOVA
Tukey's HSD
factorial ANOVA

how to use tables
APA style for results

how to interpret SPSS output for:
   1-way ANOVA (between and within)
   2-way ANOVA (between and within)