# PSY 452, Study Guide for the Final.doc - PSY 452 Study...

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PSY 452 Study Guide for the Final Chapter 14: #1. Describe the five parameters of data analysis. Parametric test: require interval or ratio data 2. Describe the procedures on how to select a particular statistical test (see Table 14-2). 3. Describe the differences between parametric and nonparametric tests; which are more powerful? Parametric test: require interval or ratio data Nonparametric tests: use nominal or ordinal data 4. Explain the purpose of a chi-square test. It determines whether the frequency of sample responses represents the frequencies we would expect in the population. When the data are nominal and the groups are independent, which means the experimenter assigns different subjects to them. 5. Define degrees of freedom . Each of a number of independently variable factors affecting the range of states in which a system may exist, in particular 6. Explain the purpose of the t test for independent groups and the t test for matched groups. Which test(s) is (are) used for between-subjects and within-subjects designs? T test for independent groups: T test for matched groups: either assigns the same subjects to both conditions or matches subjects and the randomly assigns them to either condition o A t test for matched groups may use fewer subjects and achieve greater control over individual differences that a t test for independent groups o This makes a t test for matched groups more powerful Between-subjects: is the degree to which the scores of different treatment groups differ from one another or the grand mean. Within-subjects design: is the degree to which the scores of subjects in the same treatment group differ from each other 7. Explain the purpose of the analysis of variance (ANOVA) test in terms of the F ratio, between-groups variability, and within-groups variability. Analysis of variance: when data are interval or ratio level and there is at least one independent variable with 3 or more levels F ratio: across all group means, there is a significant difference due to the IV 8. Explain the differences between: a) a one-tailed versus a two-tailed test, b) a directional versus a non-directional hypothesis, c) a Type I versus a Type II error, and d) different alpha levels. One tailed vs a two-tailed test: Directional vs a non directional hypothesis: Type 1 vs type 2 error: o Type 1: is the incorrect rejection of a true null hypothesis (false positive) o Type 2: is incorrectly retaining a false null hypothesis (false negative finding).

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Different alpha levels: the significance level, is the probability of rejecting the null hypothesis when it is true.
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