UW-Madison PSYCH 210 - Within-Subjects ANOVA (3 pages)

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Within-Subjects ANOVA



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Within-Subjects ANOVA

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Lecture number:
21
Pages:
3
Type:
Lecture Note
School:
University of Wisconsin, Madison
Course:
Psych 210 - Basic Statistics for Psychology
Edition:
1

Unformatted text preview:

PSYCH 210 Lecture 21 Outline of Last Lecture I Finish between subjects ANOVA a Hypothesis testing b Post hoc c Assumptions II New Test Within subjects or repeated measures ANOVA a Why do we need a new test Outline of Current Lecture I Within Subjects ANOVA a Calculations for F observed b Hypothesis testing steps Current Lecture II Within Subjects ANOVA a Why do we need a new test i Between Subjects F MS Between MS Within ii Within Subjects F MS Between MS Error 1 MS Error MS Within Groups Variance without individual differences a Size of denominator is decreasing for within Ss b Relative to a between Ss ANOVA within Ss is thus more powerful i Same Relationship as Independent vs RelatedSamples t test ii Doesn t work for all experimental set ups b Calculations for F observed i See handout ii Ex Counterconditioning of phobias systematic desensitization These notes represent a detailed interpretation of the professor s lecture GradeBuddy is best used as a supplement to your own notes not as a substitute 1 Use of classical conditioning 2 See template for sample data 3 CER Conditioned Emotional Response iii Independent Variable Time of Measurement 1 Common for Within Subjects Design 2 Note ANOVA can measure any of groups 3 n number of participants total and N total number of observations a Compare to Between Subjects n Number of Participants per conditions N total number of participants c Hypothesis testing steps i Calculate Step 3 of Hypothesis Test first Fobs 1 Find a SS b df c MS 2 Five pieces of variance Variance Between Groups Within Group Indv Diffs 3 4 5 6 Error Fobs MS between MS error SStotal x2 G2 N 3495 2952 32 775 47 SSwithin SS for each level 157 88 60 90 132 439 88 SSbtwn T2 n G2 N 1152 8 762 8 482 8 562 8 2952 32 335 59 7 SSindv diffs P2 k G2 N 342 4 352 4 582 4 2952 32 245 22 a No short hand way to do this a lot of work 8 SSerror SSwithin SSindv diffs 439 88 245 22 194 66 a Accounts for variability we can t attribute to any given source Leftover



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