difference or association- can figure out from hypothesis
experimental design- related=matched pairs or repeated measures unrelated= independent groups
level of measurement- nominal=categorical and discrete data, ordinal=scale, data is ordered not have equal intervals between, and interval= based on numerical scales, equal intervals, precise, and parametric tests
chi squared:
can test for difference or association
if difference the experimental design is unrelated
nominal data as data is discrete or categorical
mann whitney:
tests for a difference
unrelated experimental design
ordinal data as data is ordered or on a scale but not in equal intervals
unrelated t-test:
tests for a difference
unrelated experimental design
interval data as based on numerical scales, equal intervals
sign test:
tests for difference
related experimental design
nominal data as discrete or categorical
wilcoxon test:
tests for a difference
related experimental design
ordinal data as data is ordered but not equal intervals
related t-test:
tests for a difference
related experimental design
interval data as data is based on numerical data and has equal intervals between
spearmans rho:
tests for an association or correlation
ordinal data as data is ordered but not in equal intervals
pearsons r:
tests for an association or correlation
interval data as data is based on numerical scale and has equal intervals between
if test has an r in then calculated value needs to be higher than critical for it to be significant
if test does not have an r in then calculated value needs to be lower than critical for it to be significant