5 D. K. Aaron and V. W. Hays University of Kentucky, Lexington How many pigs? Statistical power considerations in swine nutrition experimentsD. K. Aaron and V. W. Hays University of Kentucky, LexingtonJ ANIM SCI 2004, 82:E245-E254
6 Introduction “how many replications do I need?” limited by practical or economical constraintsprimary objective to provide a means to determine # of replicatespriori, prospective vs retrospective a posteriori, power analysis
7 Why we need to determine # rep Too few replicateswaste time and resources with little chance of finding a significant effectToo many replicatesMore replicates than necessary to detect an effect (waste time and resources)
8 Classical hypothesis testing Step 1: Formulate hypothesesStep 2: Decide on Type I error rate, α Typical yet arbitrary values 0.01, 0.05Step 3: Collect and summarize data; calculate the appropriate test statisticStep 4: Determine the critical value of the test statisticStep 5: Make decision and draw conclusionsStep 6: Compute P-value and interpret
15 Some terms to learn null vs alternate or research hypothesis ↓ Type I errors to reduce false claimsstandardized effect size ff = 0.10, 0.25, and 0.40 = S, M, LPrevious work, power of 80%, educated guessPilot study, review, sci literatureCV (Coefficient of Variation) = SD/mean*100
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