Ch5: Five ANOVA Assumptions Flashcards
Three fundamental assumptions
a) the error components associated with the scores of the dependent variable are independent of one another
b) these errors are normally distributed
c) the variances across the levels of groups of the independent variable are equal
the first assumption
the residual or error component of the Yi scores (the difference between these scores and the group mean) is random and independent across individual observations
autocorrelation
the propinquity of the cases to each other in time
the second assumption
the error components associated with Yi are normally distributed
leptokurtic distribution
tends to have tails that are higher than the normal curve is and bunched in the middle, producing a peak look
platykurtic distribution
has a flatter, more evenly distributed look than the normal curve
Outliers
Standarized values exceeding +- 2.5 can be designated outliers
Central limit theorem
as increase the sample size (n), the resulting sample mean Y bar will increasingly approximate a normal distribution
homogeneity of variance or homoscedasticity
the distribution of residual errors for each group have equal variances
Three causes of heteroscedasticity
Classfication independent variables such as gender or ethnicity may have unique variances associated with the scores on the dependent variable
an experimental manupulation of an independent variable can encourage participants to behave more similariry or differently than a control condition.
variability on some dependent variables may be related to group size
floor or ceiling effect
where participants cannot score any lower or higher on the dependent measure because of intrinsic or extrinsic constraints