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20 Cards in this Set
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comparing a proportion to a hypothesized value

binomial test

comparing a proportion to a hypothesized value if sample size is large

X2 goodnessoffit test with two categories

comparing frequency data to a hypothesized value when data are approximately normal

onesample ttest

comparing median to a hypothesized value when data are not normal (even after transformation)

sign test

comparing frequency data to a discrete probability distribution

X2 goodnessoffit test

comparing data to the normal distribution

ShapiroWilk test

categorical explanatory variable and categorical response variable

contingency analysis

numerical explanatory variable and categorical response variable

logistic regression

numerical explanatory variable and numerical response variable when data are bivariate normal

linear and nonlinear regression, linear correlation

numerical explanatory variable and numerical response variable when data are bivariate normal

Spearman's rank correlation

test differences between two means for two treatments with independent samples assuming normal distribution

Twosample ttest

test differences between two means for two treatments with independent samples assuming normal distribution but unequal variances

Welch's ttest

test differences between two means for twotreatments with independent samples assuming not normal distributions

MannWhitney Utest

test differences between two means for two treatments with paired data assuming normal distribution

pairedttest

test differences between two means for two treatments with paired data assuming not normal distribution

sign test

test differences between two means for more than two treatments assuming normal distribution

ANOVA

test differences between two means for more than two treatments assuming not normal distribution

KruskalWallis test

hypothesis testing in which a computer Is used to mimic repeated sampling from an imaginary population whose properties conform to those stated in the null hypothesis. The frequency distribution of test statistics calculated on the simulated samples gives a null distribution of the test statistic.

simulation

generate the null distribution for a measure of association between two variables by randomly rearranging the observed values for one of the variables. The frequency distribution of test statistics calculated on many randomized data sets gives the null distribution of the test statistic.

randomization

calculating standard errors of estimates and confidence intervals for parameters. It uses resampling from the data to approximate the sampling distribution for an estimate.

bootstrapping
