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Final

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Carleton University

Psychology

PSYC 3000

Bruce Hutcheon

Summer

Description

For Levenes test if you find p05less than it means you have failed the test True H0 that populations samples are drawn from have the same variance p05 chance hypothesis true is less than 5 populations have different variances treatment affects varianceWhat null hypothesis is tested using Levenes test Treatment no effect on variance not about sample variances or sampleing distributions Study F11239 p072 t1223 p021 2tailed for the positiveimage group M230 sX220 compared with control M276 sX236 The samples have passed Levenes test 72 chance samples from populations with identical variances low but not low enough to reject H0 H0 truepooled variance 202362 sample variances are 12 and 16 design is balanced and therefore each weight is 12 The pooled variance is therefore 12 of the sample 1 variance plus 12 of the sample 2 variancestandard error2pooled variance 20236228 standard error sqrtpooled variancesqrtn Dffreedomsay total number of observations is N14 balanced design we must have n7 sesqrt28sqrt72 dlarge corresponding t value will have p05 False Even large effect may not be significant if not enough power sample too smallPopulation Mean 50 SD15 sample N35 M425cohens d Single sample d 5042515 05 Sample size not needed1975 84 hours on hmwk32 SD 2003 7132 d 847132 041 Repeated measures matched pairs mean difference 5 SD before 8 after 12Pool SD by converting to variance take average and convert back to SDVariances 64 144 Average 641442104 pooled variance Pooled SD about 10 D 51005 Cohens d for ind samples N 11 M15 SD5 N6 M20 SD4Mean diff5 SD 54 pool Convert to variances25 16 Total df 116 215 10 23 and 5 13 for samples Pooled variance 2325 1316 22 Square to get pooled SD 469 d5469 107 balanced design Each sampledf Pooled variance is average of ind Sample variance 25162 453 d 5453 Ind Samples M1M26 t183 p008 equal sample sizes T MDSE T3 therefore SE 632 SE s polledsquare root 2n2 spooledsquare root 210 S pooled 2045444 d 6444 135You can increase the power of a test by decreasing the alpha level FD AlphaD rejection regions D power All else being equal the larger the sample size the greater the value of the noncentrality parameter T Depends on sqrt of sample size so greater n greater NCP greater powerPower is the probability of rejecting the null hypothesis when it is false TBetaprobability rejecting H0 when it is false F chance commit type 2 error accept H0 when falseWhen are you susceptible to criticism that you do not have enough power in a ttest When accept H0 always chance youre wrong T2E Power addresses tells chance of T2E low power high chance T2E

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