Study Guide for Research Methods in Personality and Social

THINGS TO INCLUDE IN AN EXPERIMENT

• PREVIOUS RESEARCH - WHAT STUDIES YOU WOULD WANT TO LOOK IN TO
• WHY YOU WOULD WANT TO DO THE STUDY
• IRB APPROVAL, ETHICAL CONCERNS
• COVER STORY
• iNFORMED CONSENT
• HYPOTHESIS
• PARTICIPANTS - HOW MANY ARE YOU HOPING FOR, EFFECT SIZE
• DEMOGRAPHICS
• QUESTIONNAIRES - VALIDITY, RELIABILITY
• DEBRIEFING
• ANALYSIS - SEE NEXT FEW SLIDES
• FUTURE RESEARCH AND IMPLICATIONS

T TEst

• paired
• (repeated measures) (within) samples vs. independent samples (between subject)
• can be used to determine if two sets of data are significantly different
• from each other
• go back to look at means to see where the greatest differences and significance is

ANOVA

• One-way ANOVA is used to test for differences among two or more independent groups (means),e.g. different levels of
• urea application in a crop, or different levels of antibiotic action on
• several bacterial species or
• different levels of effect of some medicine on groups of patients.
• Typically, however, the one-way ANOVA is used to test for differences
• among at least three groups, since the two-group case can be covered by
• a t-test
• When there are only two
• means to compare, the t-test and
• the ANOVA F-test are
• equivalent; the relation between ANOVA and t is given
• by F = t2.
• Factorial ANOVA is used when the experimenter wants to study the
• interaction effects among the treatments.
• Repeated measures ANOVA is used when the same subjects
• are used for each treatment (e.g., in a longitudinal study).
• Multivariate
• analysis of variance (MANOVA) is used when
• there is more than one dependent variable.

CORRELATIONS

• Only looks at at the relationship between to variables
• Pearson's correlation test the most common used

NON PARAMETRIC TESTS

• statistics not based on parameterized families of probability distributions. They include both descriptive and inferential statistics.
• Typical
• parameters are the mean, variance, etc.
• Unlike parametric statistics, nonparametric statistics make no assumptions about the probability distributions of the variables being
• assessed