Download Chapter 1 of Gleitman et al

Research methods in psychology: Design and data analysis Study Guide
Chapter 1 of Gleitman et al., pp. 12-33
And conferences of Th/Fri Aug 30/31. See also Reading Guide for Strack et al.
The terms in bold are particularly important. They will be used frequently, by all instructors,
throughout the year.
The empirical approach
formulating testable hypotheses
anecdotal evidence
reporting bias
observation
confirmation bias
previous literature (theories and data)
file-drawer problem (a type of reporting bias)
defining the independent and dependent variables
collecting the data (see below)
evaluating the data (see below)
drawing conclusions
confirming the hypothesis (NOT proving, see p. 14)
disconfirming the hypothesis
suggesting further avenues of study
replications
elaborations
formulating new hypotheses
collecting the data: types of research designs
experiments
between-group designs
random assignment to groups
“matched” assignment to groups (example in second paragraph of p. A1)
within-subject designs
case studies
observational studies
correlational studies
direction of causality
third variable problem
collecting the data: internal validity
associated with the independent variable(s)
proper selection of the "control" condition
minimizing demand characteristics
double-blind design
eliminating confounds
counterbalancing (example in last paragraph of p. 21)
associated with the dependent variable(s)
does the dependent variable measure what you want it to?
scales: categorical, ordinal, interval, ratio (see pp. A2-A4)
Psy 121
Fall, 2007
Study Guide
2
defining the independent and dependent variables: external validity
selecting the sample
ecological validity
ethics in psychology research
informed consent
debriefing
evaluating the data: GRG Appendix
And conferences of Thurs/Fri Sept 6/7
frequency distributions, histograms
normal distributions
skewed distributions
measures of central tendency: mean, median, mode
measures of variability
range
variance
standard deviation
statistical tests
correlation coefficient (r)
positive and negative correlations
correlation does not imply causation
hypothesis testing
null hypothesis
“critical ratios”:
t-test: comparison of two means (one indep variable with two levels)
two independent means (between-groups design)
paired means (within-subjects design)
Analysis of variance (ANOVA, F-test)
comparisons involving more than two means
one independent variable with more than two levels
more than one independent variable
main effects
interactions
p-value (probability)