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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 goodness-of-fit test with two categories comparing frequency data to a hypothesized value when data are approximately normal one-sample t-test 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 goodness-of-fit test comparing data to the normal distribution Shapiro-Wilk 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 Two-sample t-test test differences between two means for two treatments with independent samples assuming normal distribution but unequal variances Welch's t-test test differences between two means for two-treatments with independent samples assuming not normal distributions Mann-Whitney U-test test differences between two means for two treatments with paired data assuming normal distribution paired-t-test 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 Kruskal-Wallis 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