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ANOVA:
Analysis of Variance

Factor:
the variable (independent or quasiindependent) that designates the groups being compared in analysis of variance

Levels:
the individual conditions or values that make up a factor

Between treatments variance:
variability in scores that is due to differences between the levels of the independent variable

Within treatments variance:
variability in the scores that is due to measurement error or individual difference (chance)

Mean squares:
term used to describe variance in ANOVA

Fratio:
the test statistic for the ANOVA

Error term:
the denominator of the Fratio; provides a measure of variance due to chance

Post hoc tests:
additional hypothesis tests that are done after an analysis of variance to determine exactly which mean difference are significant and which are not

Experimentwise alpha level:
the overall probability of a Type 1 error that accumulates over a series of separate hypothesis tests – usually substantially greater than the stated or “nominal” alpha for any of the individual tests

eta squared (h2):
percentage of variance in dependent variable accounted for by the manipulation (Independent variable)

Estimation:
the inferential process of using sample statistics to estimate population parameters

Point estimate:
a single number used as an estimate of an unknown population parameter

Interval estimate:
a range of values that is used as an estimate of an unknown population parameter

Confidence interval:
an interval estimate that is accompanied by a specific level of confidence or probability

Repeated measures study:
withinsubjects study  a study in which a single sample of individuals is measures more than once on the same dependent variable

Matched subjects study:
each individual in a sample is matched with an individual in the other sample; subjects are matched either because they are similar on a variable of interest (e.g., IQ, sex)

Difference score:
D = X1 – X2 – the difference between the matched scores (i.e., between the first and second scores of an individual in a repeated measures design or between the scores of the two related individuals in a matched subjects design)

Estimated standard error for MD:
the average or typical distance of a single difference score from the population difference score

Carryover effects:
participant’s response in the second treatment is altered by lingering aftereffects of the first treatment

Progressive error:
participant’s performance or response changes consistently over time

