statistical tests

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