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### 19 Cards in this Set

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 Independent samples When two ore more groups consist of completely different individuals Dependent samples Matched pairs - when the same individuals are tested more than one time Parametric data Data are normally distributed - greatly increased power of statistical analysis Nonparametric data Not normally distributed - categorical data (nominal or ordinal) What are the qualifications for parametric data? 1. Measured variable must be normally distributed 2. Samples must be drawn at random 3. Variances in samples being compared must be equal 4. Data must be measured on interval or ratio scales (ie: continuous) Concept of Robustness If a sample is large enough, parametric tests can withstand slight variations from parametric assumptions. T-tests 2 groups only, 1 dependent and independent variable Independent + Parametric (2 groups only) Independent + Nonparametric (2 groups only) Independent t-test Mann-Whitney U (ranks) Dependent + Parametric (2 groups only) Dependent + Nonparamentric (2 groups only) Paired t-test Wilcoxon (ranks) Why can't you run mulitple t-tests? Increases chance for type I error (easier to find significant result) What are ANOVAs? Mean differences between more than 2 groups Independent + Parametric (+2 groups) Independent + Nonparametric (+2 groups) One-Way ANOVA Knuskai-Wallace (ranks) Dependent + Parametric (+2 groups) Dependent + Nonparametric (+2 groups) Repeated Measures ANOVA Friedman's (ranks) Post-Hoc Tests definition Only if an ANOVA is significant, can post-hoc tests be used to determine which specific groups are different using pairwise comparissons Post-Hoc Tests examples Tukey test, Newman-Keuis (NK) test, Bonferroni t-test (Dunn's), Scheffe's comparisons Correlation coefficient (r) Used to determine the strength of relationship - goodness of fit line -1 = perfect negative relationship 1 = perfect positive rel 0=no relationship) Regression Used to describe a predictive relationship between a dependent (Y) variable and an independent (X) predictor variable Regression line Y = a +b(x) b-slope of line, rate of change in Y with one unit of X Distributions chi square - nonparametric statistic used to determine if a distribution of observed frequencies differs from expected frequencies of population