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Chapter 11

PSYC202 Chapter 11 T Statistic for 2 Related Samples.docx

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Department
Psychology
Course
PSYC 202
Professor
Ronald R Holden
Semester
Fall

Description
PSYC202 Chapter 11 – T­Test for 2 Related Samples 11.1 Introduction to Repeated­Measures Designs ­ Repeated Measures/Within­Subject Design: single sample of individuals is measured  more than once on the same dependent variable. ­ Matched­Subjects Study: each individual in one sample is matched with another  individual in the other sample (ex. Age, sex, race, IQ) 11.2 The t Statistic for Repeated­Measures Research Design ­ Get values for same individuals before treatment (X ) and after treatment (X ) then find  1 2 the difference between the scores [D=X ­X ] 2 1 ­ Number of D­scores becomes ‘n’, calculate sample mean (M ) and SS vDlue for D ­ Null hypothesis states that the mean difference for the general population is 0 ­ H 0 µ D0  ▯mean doesn’t have to be exactly 0 but has to be significantly  greater than 0 to reject the null hypothesis ­ t = M D ­ D▯  s MD calculated same as estim. standard error in single statistic t test          s   MD  11.3 Hypothesis Tests and Effect Size for the Repeated­Measures Design ­ Cohen’s d for repeated measures study = µ D           D  σ ­ In repeated measures, sample variability describes the consistency of the  treatment effect. Ex. If treatment constantly adds 7­8 points to each individual’s  score, the set of difference scores will be clustered around a mean of M=8 with  little variability.  ▯Larger variability changes t­value, and brings it closer to mean  and further from critical regions, making it harder to reject null
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