PSYC 2301 Lecture Notes - Lecture 10: Repeated Measures Design, Pooled Variance, Null Hypothesis
Document Summary
10. 1 independent-measures design introduction: most research studies compare two (or more) sets of data. Data from two completely different, independent participant groups (an independent-measures or between-subjects design) 10. 2 independent-measures design t statistic: null hypothesis for independent-measures test, alternative hypothesis for the independent- measures test. Independent-measures hypothesis test formulas: basic structure of the t statistic. M s (m1 t = [(sample statistic) (hypothesized population parameter)] divided by the estimated standard error. Estimated standard error: measure of standard or average distance between sample statistic (m1-m2) and the population parameter, how much difference it is reasonable to expect between two sample means if the null hypothesis is true (equation 10. 1) s. Pooled variance: equation 10. 1 shows standard error concept but is unbiased only if n1 = n2, pooled variance (sp2 provides an unbiased basis for calculating the standard. Degrees of freedom: degrees of freedom (df) for t statistic is df for first sample + df for second sample df df.
