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one sample z-test
one sample and the population standard deviation is known, to see how “extreme” the sample is
one sample t-test
one sample, but the population standard deviation is unknown, to see how “extreme” the sample is
dependent samples t-test
two measures of the same people, you are looking for difference in scores (matched samples, repeated measures)
independent samples t-test
two samples, comparing the two sample means
one-way anova
2+ samples with 1 predictor/ independent variable
two-way anova
2+ samples with 2 predictors/ independent variables
correlation
there is 1 continuous predictor, you are seeing if x and y are related in any way (is there a relationship)
simple linear regression
there is 1 continuous predictor, you are seeing if x predicts y (predicting the relationship)
multiple regression
2+ continuous variables, you are predicting the relationship of multiple variables
chi square “goodness of fit” test
looking for any difference in frequency of 1 categorical outcome, participants can only belong to one group or another
chi square test of independence
looking to predict frequency of 1 categorical outcome using another variable, participants can only belong to one group or another
Note 
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