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PSY201H1 (45)
Chapter 11

Chapter 11

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Department
Psychology
Course
PSY201H1
Professor
Gillian Rowe
Semester
Fall

Description
Chapter 11 The t Test for Two Related Samples 111 Introduction to RepeatedMeasures DesignsRepeatedmeasures designwithinsubject designone in which a single sample of individuals is measured more than once on the same dependent variable The same subjects are used in all of the treatment conditionstwo sets of data are obtained from the same sample of individuals ex group of patients measured before therapy and after therapyResults wont be biased between samples because using the same individuals in all conditionsMatchedsubjectsstudy in which each individual in one sample is matched with an individuals in the other sample The matching is done so that the two individuals are equivalent or nearly equivalent with respect to a specific variable that the research wants to controltwo separate samples with one from each sample being matched ex study for verbal learning match in terms of gender and IQmale with IQ of 120 matched with other male with IQ of 120 y Can match on more than one variableage gender race IQ etcIn both cases the data consist of two sets of scores with the scores in one set directly related onetoone with the scores in the second setthe two research designs are statistically equivalent and are grouped together under the name relatedsamples designs 112 The t Statistic for a RepeatedMeasures Research Design Difference Scores The Data for a RepeatedMeasures StudyDifference scoresDdifference between the first score and the second score for each individual subtract first score before treatment from the second score after treatmentSign of D tells you the direction of the change to compute the t statistic the number of D scores nwill be used as well as the sample mean M and the value of SS for the sample of D scoresDThe Hypothesis for a RelatedSamples TestResearcher wants to known if theres any difference between the two treatment conditions for the general populationinterested in a population of difference scoresNull hypothesis states the mean difference for the general population is zeroH0o D y Even when the null is true still expect some individuals to have positive difference scores and some to have negative difference scores individual scores not all equal to 0 y Will be some error between a sample mean and the population mean even if the null is truewe do not expect Mto be exactly equal to 0 DAlternative hypothesis states theres a treatment effect that causes the scores in one treatment condition to be higherlower than the scores in the other conditionH0D The t Statistic for Related SamplesUse sample mean as basis for testing hypotheses about the population mean Repeated measures t testtMsdealing with difference scores not X valuesD D MD
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