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### 63 Cards in this Set

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 Variance SS/(N-1) Standard Deviation square root of SS/(N-1) Standard Error of the Mean standard deviation of the population/square root of N it is the standard deviation of the sampling distribution of the mean Power 1-beta where beta is the type II error (the odds of retaining the null hypothesis when it is really false; or the odds of saying there is no result/difference when there really is one) single-sample chi-square 1 variable, nominal data multiple-sample chi-square 2 or more variables, nominal data Mann-Whitney U test 2 independent groups, ordinal data Wilcoxon matched-pairs test 2 correlated groups, ordinal data Kruskal-Wallis test 2 or more independent groups, ordinal data t-test for single sample sample vs. population for interval/ratio data t-test for correlated samples 2 correlated groups, interval/ratio data t-test for independent samples 2 indepedent groups, interval/ratio data one-way ANOVA 1 IV, 2 or more independent groups, interval/ratio data factorial ANOVA 2 or more IVs, interval/ratio data repeated measures ANOVA 2 or more correlated groups, interval/ratio data Variance SS/(N-1) Standard Deviation square root of SS/(N-1) Standard Error of the Mean standard deviation of the population/square root of N it is the standard deviation of the sampling distribution of the mean Power 1-beta where beta is the type II error (the odds of retaining the null hypothesis when it is really false; or the odds of saying there is no result/difference when there really is one) single-sample chi-square 1 variable, nominal data multiple-sample chi-square 2 or more variables, nominal data Mann-Whitney U test 2 independent groups, ordinal data Wilcoxon matched-pairs test 2 correlated groups, ordinal data Kruskal-Wallis test 2 or more independent groups, ordinal data t-test for single sample sample vs. population for interval/ratio data t-test for correlated samples 2 correlated groups, interval/ratio data t-test for independent samples 2 indepedent groups, interval/ratio data one-way ANOVA 1 IV, 2 or more independent groups, interval/ratio data factorial ANOVA 2 or more IVs, interval/ratio data repeated measures ANOVA 2 or more correlated groups, interval/ratio data mixed ANOVA independent and correlated groups, interval/ratio data ANCOVA removes extraneous variables, interval/ratio data randomized block ANOVA extraneous variables, interval/ratio data trend analysis quantitative IV, interval/ratio data MANOVA 2 or more dependent variables, interval/ratio data SST (sum of squares total) SST = SSB + SSW sum of squares between plus sum of squares within MST (mean squares total) MST = SST/df F F=MSB/MSW F=(treatment+error)/error Pearson Product Moment (r) variable 1 = interval or ratio variable 2 = interval or ratio Spearman Rank-Order (rho) variable 1 = rank-ordered variable 2 = rank-ordered Phi variable 1 = true dichotomy variable 2 = true dichotomy Tetrachoric variable 1 = artificial dichotomoy variable 2 = artificial dichotomy Contingency variable 1 = nominal variable 2 = nominal Point Biserial variable 1 = true dichotomoy variable 2 = interval or ratio Biserial variable 1 = artificial dichotomy variable 2 = interval or ratio Eta Used to assess non-linear relationships variable 1 = interval or ratio variable 2 = interval or ratio LISREL linear structural relations analysis used when a causal model involves recursive (one-way) and non-recursive (two-way) paths examines the relationship between observed variables and takes into account latent traits the variables are believed to measure and the effects of measurement error Path analysis translating a theory about the causal relationships into a path diagram p (item difficulty) total number of examinees passing the exam/total number of examinees p=0.5 optimal unless true false test...then p=0.75 optimal Item Characteristic Curve (ICC) constructed for each item information on the relationship between an examinee's level on the ability or trait and the probablity that they will respond to the item correctly Item Response Theory (IRT) the latent trait model test scores are reported in terms of an examinee's level on the trait being measured rather than in terms of a total test score makes it possible to equate scores from different sets of items and from different tests Spearman-Brown prophecy formula provides an estimate of what the reliability coefficient would have been had it been based on the full length of the test (or used to say what it would be if the tests were lengthened or shortened) Cronbach's coefficient alpha average reliability that would be obtained from all possible splits of the test Kuder-Richardson Formula 20 (KR-20) coefficient alpha (split half measure of internal consistency and reliability) used when items are scored dichotomously kappa statistic or coefficient concordance inter-rater reliability Standard Error of the Measurement =standard deviation of the test scores multiplied by the square root of 1 - the reliability coefficient used to calculate the confidence interval multitrait-multimethod matrix to test convergent and discriminant validity correlations with different methods of the same trait and the same methods of different traits methods for assessing construct validity orthogonal factors are uncorrelated oblique factors are correlated base rate (true positive + false negatives)/total number of people positive hit rate true positive/total positive validity and reliability relationships validity is less than or equal to the reliability z =(score-mean)/SD