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### 58 Cards in this Set

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 Spearman correlation and Pearson chi-square are two examples of … non-parametric statistics Non-parametric statistics should be typically used when the dependent variable is ____ ordinal with 4 or fewer points; ranked data; nominal; highly skewed (>2.0) (4 marks) Non-parametric tests are not as _____ as parametric tests. strict Non-parametric tests do not test hypotheses about … mean differences. Technically, in the context of group differences, the non-parametric statistic null hypothesis is that the data have been sampled from … identical populations Non-parametric statistics assume that the _____ of the distributions are homogeneous. shapes Kruskal-Wallis assumes _____ of variance. homogeneity In the context of non-parametric statistics, there is a _____version of Levene’s test of homogeneity of variance. median-based Technically, we should not apply parametric statistics on data scored on _____ scales. Likert If data are Likert in nature and have ______ points in the scale, it may be argued to be justifiable to apply parametric statistics to them. 5 or more Non-parametric statistics should always be applied to ____ data. ranked Although simulation research shows that the accuracy of parametric statistics is fairly good in cases where the ordinal scale has 5 or more points, this research assumes that _____, which is ___ in practice. all points in the scale are used; often not the case (2 marks) The Kruskal-Wallis test is based on transforming the original dependent variable data into ______. ranks. Strictly speaking, the Kruskal-Wallis null hypothesis is that the groups have … identical population distributions Differences in group ______ may be implied by a statistically significant Kruskal-Wallis statistic. mean ranks The notion that a difference in group medians may be implied by a statistically significant Kruskal-Walliss statistic is based on … strict assumptions being met. In order to test the assumption of normally distributed data, many people use a statistic called … Shapiro-Wilks. The problem with statistics such as Shapiro-Wilks for testing distributions for “sufficient normality” is that they are … excessively powerful In order to get SPSS to conduct the median-based version of Levene’s test of homogeneity of variance, one must use the ____ utility and then select the _____ option. Descriptives --> Explore; power estimation within the Plots window (2 marks) Kruskal-Wallis is essentially based on ____ and then _____the summed ranks within each group. summing; squaring (2 marks) What effect size estimate does SPSS calculate for Kruskal-Wallis? None Effect size for Kruskal-Wallis can be calculated by… dividing the chi-square value by N -1 (2 marks) Like ANOVA, Kruskal-Wallis is an ______ statistic. omnibus Typically, if a researcher obtains a statistically significant Kruskal-Wallis, the researcher will follow-up with a series of … Mann-Whitney tests. The Mann-Whitney test should be ____, given the existence of _____. dead; Kruskal-Wallis The Mann-Whitney test is a non-parametric equivalent of the … independent samples t-test. The Mann-Whitney test tests the null hypothesis that the _____ are equal. mean ranks What is the Mann-Whitney value associated with the SPSS table below? 6.00 From what analysis is the below window in SPSS? Mann-Whitney From what analysis the below window in SPSS? Kruskal-Wallis What estimate of effect size does SPSS calculate for Mann-Whitney test? none. What is the eta squared formula for the Mann-Whitney test? Z squared divided by N-1 (2 marks) An alternative to conducting a series of Mann-Whitney U tests as a follow-up to a significant Kruskal-Wallis is to conduct a … Jonckheere-Terpstra test The Jonckheere-Terpstra test is really just a… trend analysis for mean ranks. In the SPSS window below, what two tests are missing from the ‘Test Type’ box? Kruskal-Wallis; Jonckheere-Terpstra (2 marks) The effect size estimate reported by SPSS for the Jonckheere-Terpstra test is referred to as… there is none. An effect size statistic that can be calculated by hand based on the Jonckheere-Terpstra statistic is known as…. eta squared The following formulate can be used to calculate effect size for the Jonchkeere-Terpstra statistic…. Z2/(N-1) Friedman’s ANOVA does not assume ______ data. normally distributed Friedman’s ANOVA can be used on data that conform to a ____ factor. within-subjects One of the limitations of the Friedman ANOVA test is that there is no _____ version of it. factorial Given the existence of Friedman’s ANOVA, _____ should be dead. Cochran's Q Referring to Friedman’s ANVOA as an ANOVA is a … misnomer. The Friedman ANOVA statistic converts the dependent variable into … ranks. When you really get down to it, Friedman’s ANOVA may be considered a test of ... consistency. In the SPSS window below, what two tests are missing from the ‘Test Type’ box? Friedman’s ANOVA; Cochran’s Q (2 marks) The formula to estimate effect size in the Friedman ANVOA case is… chi-square/((N)(k-1)) (2 marks) In the context of conducting a Friedman’s ANOVA, the effect size estimate is known as …. Kendall’s W Given that _______ is a measure of effect size, and you can get exactly the same p value for this effect size in SPSS, there is really no need to conduct a … Kendall’s W; Friedman’s ANOVA (1 mark; yes, 1 mark) The ______ is a non-parametric equivalent of the dependent samples t-test. Wilcoxon-Signed Rank Test The ______ could be used as a post-hoc test in the Friedman omnibus statistic scenario. Wilcoxon-Signed Rank Test Given the existence of Cochran’s Q, ____ should be dead. McNemar chi-square Given the existence of Friedman’s ANOVA, _____ should be dead. Cochran’s Q. Many non-parametric statistics do in fact assume … homogeneity of variance. Non-parametric statistical analyses are often _____ than the corresponding parametric statistical analyses. less powerful One of the main limitations associated with non-parametric statistics is that you can’t use them to test … interactions. In practice, all too often, non-parametric statistics are not actually the solution to our … statistical problems. Between-groups ANOVA is to Kruskal-Wallis as repeated measures ANOVA is to… Friedman ANOVA