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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