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| used to determine if there are significant differences between 3 o more means |
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| mean values/ mean square difference |
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| variance in numerator/variance in denomenator |
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| Orthogonal comparison- means in different directions do this test |
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| accounts for type 1 error |
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| using the G for only 2 groups in post hoc helps control for this |
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| analyses of variance in which more than one factor is employed, test for sig diff b/t groups for each factor and interactions, and instead of only 1 SS, we now have 3 |
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| the effect of solely the IV ( A or B) |
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used with 2 or more variables that exist in the real world so there is no experimental manipulation, no IV, no DV.
desribes and measures the direction and degree of relationship b/t 2 or more variables. gather data on individuals instead of testing differences b/t means of diff groups |
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| df for pearson's coefficient |
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| measure of central tendency for data that is plotted, predict values of other variables, high correlation lets it predict, |
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| variance (differences) b/t sample means over variances with no treatment effect |
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| what is being accounted for in numerator of Anova |
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| mean difference describes this |
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| measures direction of relationship, form of relationship, and strength/consitency of relationship |
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| degree which x and y vary together/ how they vary separately |
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| used for prediction, validity, reliability, theory verification |
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non parametric tests since they make few if any assumptions about the population distribution
less sensitive than parametric tests since there is a better chance of type 2 error
uses nominal and ordinal data |
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| chi square goodness of fit |
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| data values that are known |
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| chi square for independence |
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| same test as goodness of fit but different purpose, see if there is a difference between 2 groups on a particular variable. |
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| chi square of independence |
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| more likely to not see an effect |
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| the difference b/t goodness of fit and independence |
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