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t-tests and ANOVA

DefinitionTerm
Involved using two sample means to make an inference about two population means Independent -Samples t-test
Conditions that need to be met for the tests to be valid Assumptions
Populations have equal variances Homogeneity
If some assumptions are violated... the test is no longer valid
Minimal impact of heterogeneous variance, assuming equal Robust (not a big deal)
s^2/largest/ s^2 smallest Fmax
t= observed difference between sample means / standard error of the difference between the means Formula for Independent t-test
Paired-samples t) Used to examine change in scores within individuals across repeated assessments *same subjects twice* Dependent samples t-test
observed difference between 1st and 2nd and variable mean / standard error of the difference between the means Formula for Dependent t-test
The number of values in your data that are free to vary after certain rules are applied Degrees of freedom
A measure of how strong or big the relationship or difference is Effect size
Hypothesis test that allows you to examine mean differences between two or more groups on a numeric DV ANOVA
A categorical independent variable that designates group Factor
Individual conditions or categories WITHIN the factor Level
Having one factor one way anova
If levels are between subjects one-way between subjects
One factor with levels within subject one-way within subjects
More than one factor Factorial
Assumes that the error is normally distributed Normality
Breaking down the total variation Partioning the variance
Represents the sum of squared deviations between one group means and the grand mean SSb
The mean of all scores in all the groups combined on the dependent variable Grand mean
Represents the sum of the squared deviations between individual scores and their respective group means on the dependent variable SSe (sum of squares errors)
Created by: user-1998865
 

 



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