 Experimental Psychology

Review, Exam II

Chapter 9 – Using Statistics to Answer Questions

Levels of measurement

Measures of central tendency (for nominal, ordinal, and interval/ratio sets of data)

Measures of variability (apply & understand SD and variance)

Abscissa vs. ordinate axes

Types of graphs – bar and histogram

Standard normal distribution (characteristics)

Normal curve – simulation of all frequency distributions with large enough sample

Correlational relationships

Degrees of freedom

t-test – two uses

Significance level; 1-tailed vs. 2-tailed tests

Type I and Type II errors – how to minimize

Effect size (correlations & t-tests)

Chapter 10 – Experiments with 2 Groups

Structure of design

Group assignment (random or matched); if neither of these is used, groups are non-equivalent

Benefit of correlated groups designs - why they reduce error variability; know types (matched,

repeated measures, natural sets)

Statistic (t-test or ANOVA) = between groups/within groups (know relationship of between-

groups to within-groups)

t-test (independent samples and correlated samples) – correlated samples should have positive

correlation; requires interval or ratio level of measurement

Robustness of t-test (assumption of homogeneity)

Computer output – interpretation; be able to identify the type of test and # participants

Importance of internal validity; cause/effect relationships

Chapter 11 – Experiments with Multiple Groups

Structure of design – know how to identify names (example: “2 x 3 ind. Grps.” or “one-way”

design)

Group assignment

Statistic = between groups/within groups

One-way ANOVA (completely randomized and repeated measures) – requires interval or ratio

level of measurement

Problems with repeated measures designs

Mean squares (SS/df), F ratio (between grps MS / within grps MS), and Post hoc tests (identify

where the difference is)

Asymptomatic

Computer output – interpretation