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### 67 Cards in this Set

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 E.g. nominal scale sex eye colour DSM diagnosis religion i.e. unordered categories E.g. ordinal scale likert scale i.e. categories and rank order E.g. interval scale IQ scores temperature i.e. rank order and equal intervals can add & subtract What type of measurement? 1. religion 2. IQ score 3. DSM diagnosis 4. height 5. gender 6. likert scale 7. reaction time 8. frequency of agressive acts 1. nominal 2. interval 3. DSM diagnosis 4. interval 5. nominal 6. ordinal 7. ratio 8. ratio E.g. ratio scale # calories consumed reaction time i.e. rank order, equal intervals AND absolute zero can multiply & divide Types of measurement in increasing complexity N ominal O rdinal I nterval R atio Cumulative frequency total number observations that fall at or below each score Kurtosis the relative peakedness of a distribution more peaked = leptokurtic more flat = platykurtic Skewed distribution more than half observations fall on one side of distribution postive = low score negative = high score Measure of central tendancy mode (Mo) median (Md) mean (M or X) Relationship bet measures of central tendency in skewed distributions positively skewed d: mean, greater than median, greater then mode negatively skewed d: mode, greater than median, greater than mean Measures of variance range variance standard deviation Def: variance a measure of variability calculated by dividing the sum of squares SS / n (population) SS / n-1 (sample) Def: standard deviation square root of the variance a measure of variability of scores around the mean SS / n - then take square root Re: Inferential statistics, What is a sample statistic used for to estimate a population parameter Sampling error random error responsible for diff bet sample values and population Sampling distribution of the mean distribution of means obtained if large number of equal-size random samples are drawn from same population 3 predictions of Central Limit Theorem 1. as sample size increases, sample distribution of mean approaches normal distribution 2. mean of sampling distribution of the mean = population mean 3. SD of sample distribution of the mean = population SD divided by square root of sample size Def: Standard error of the mean What does it measure SD of sampling distribution of the mean variability due to effects of random error What happens to standard error when 1. SD larger & sample size smaller 2. SD samller & sample size larger 1. SE larger 2. SE smaller 2-tailed vs 1-tailed hypothesis 2-tailed = nondirectional 1-tailed = directional rejection / critical region region of unlikely values lies in one or both tails of sampling distribution values occur as a result of sampling error retention region region of likely values lies in central portion of sampling distribution What happens to hypotheses if sample statistic is in rejection region null hypothesis is rejected alternate hypothesis is retained What happens to hypotheses if sample statistic is in retention region null hypothesis is retained alternate hypothesis is rejected Size of rejection region defined by... alpha level of significance note: alpha = 0.05 means 5% in rejection region Type I error reject a true null hypothesis Type II error retain a false null hypothesis Statistical "confidence" certainty about the decision re: null hypothesis Statistical "power" ability to reject a false null hypothesis Parametric tests evaluate hypotheses about population means, variances etc. e.g. t-test, ANOVA interval or ratio scale non-parametric tests evaluate hypotheses about shape of distribution e.g. Mann-Witney U test, Wilcoxon ordinal or nominal scale degrees of freedom N-1 (t-test) C-1 (chi-square) What information do you use to select an inferential statistic? scale of measurement dependent variable study design What statistical test would you use for nominal data? single-sample Chi-square multiple-sample Chi-square What statistical test would you use for ordinal data? Mann-Witney U-test Wilcoxon matched pairs test Kruskal-Wallis test What are the non-parametric alternatives to: 1. independent t-test 2. correlated t-test 3. one-way ANOVA 1. Mann-Witney 2. Wilcoxon 3. Kruskal-Wallis What statistical tests would you use for interval and ration data? t-test ANOVA Name types of t-test simple sample independent samples (between) correlated samples (within) Name types of ANOVA one-way factorial (2-way, 3-way) randomized block factorial ANCOVA repeated measures mixed (split-plot) MANOVA When use one-way ANOVA vs. factorial ANOVA? one-way = 1 IV factorial = 2+ IVs What are the Post Hoc tests for ANOVA? Scheffe's S test Tukey's HSD test Fisher's LSD test Which Post Hoc test is least vulnerable to Type I Error, but more vulnerable to Type II error? Scheffe's Tukey's Which Post Hoc test is least vulnerable to Type II Error, but more vulnerable to Type I error? Fisher's The numerator of the f-ratio is a measure of variablity due to...? treatment effects & error In ANOVA, the "mean square within" provides info about: sampling fluctuations Why use one-way ANOVA instead of seperate t-tests? to reduce Type I error rate How do you calculate f-ratio? MSB/MSW How do you calculate MSB? SSB/df How do you calculate MSW? SSW/df Use: MANOVA 1+ IV 2+ DV (interval/ratio) *helps increase statistical power by assessing effects of IV on all DVs Ex: planned "a priori" analysis (4) Dunn-Bonferroni t linear contrasts orthogonal comparisons trend analysis Axis on scattergram X = IV = predictor Y = DV = criterion Which correlation coefficient is most commonly used with... 1. interval and ratio data 2. rank data 3. nominal data 1. Pearson r (also Eta) 2. Spearman rank 3. Contingency (C) How do you translate correlation coefficient score into something meaninful? calculate coefficient of determination to provide a measure of shared (explained) variability. - square the coefficient e.g. if coefficient is .60, .60 x .60 = .36, .36 x 100 = 36%, therefore, 36% of scores on DV explained by IV... remaining 64% is unexplained variance. Use: regression analysis to predict a score on a criterion (DV) based on person's obtained score on predictor (IV). How do you locate a regression line least squares criterion Use: multiple regression 2+ continuous or discrete predictors 1 criterion Ex: multiple regression 1. simultaneous (simple) 2. stepwise 3. hierarchical When use multiple regression instead of ANOVA? if groups are unequal in size if IVs on a continuous scale Use: canonical correlation [an extension of mult reg] 2+ continuous predictors 2+ continuous criterions Ex: multivariate techniques (4) multiple regression canonical correlation discriminant function analysis logistic regression Ex: bivariate correlational techniques (2) scattergram correlation coefficient Ex: bivariate prediction (1) regression analysis Ex: multivariate techniques (2) path analysis LISREL Ex: correlation & prediction tehcniques (4 main) bivariate correlational techniques bivariate prediction multivariate techniques: correlation & prediction multivariate techniques: causal modeling Use: discriminant function analysis 2+ continuous predictors 1 discrete criterion