BIOL 570 1nd Edition Lecture 9Outline of Last Lecture I. 7 steps of hypothesis tests a. hypothesesb. test statisticc. null distributiond. P-valuee. alphaf. reporting resultsOutline of Current Lecture I. Review of hypothesis testingII. Type I and Type II errorsIII. PowerCurrent LectureType I and Type II errors (p 137)RealityDecision HO true HO falseReject HOType I error correctDo NOT reject HOCorrect Type II error Do not reject (P > α)Reality HO is true Reject (P < α); Type I errorType I error, α (alpha = .05)- To reduce Type I error reduce alpha- Reducing alpha increases the chance of Type II errorThese 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.α = probability (choose alpha prior to study) Do not reject; Type II errorReality HO is false Reject Type II errorOccurs when:- Small sample size (not enough evidence)- Large amount of variability Also leads to standard error SE = S/ sqrt (n)1) Understand issue2) Reasonable value of alpha (α = 0.05)3) Increase power of the study a. Power = 1- Type II errorLabn = 15 n = 1506/15 right (40%)9/15 lefDo NOT reject RejectP = 0.607 P = 0.0176Two sided test/ Two tailed testHO: P = .5HA: P ≠ .5One sided (one tailed) test ← discouraged 1) Not commonly used2) Only in a rare situation where the other tail is essentially impossible or very unlikely3) Must decide to do a one sided or two sided test before the study is doneHO: proportion of correct answers = .5 P = .5HA: proportion of correct answers > .5 P > .51 tailed test:P = probability of getting data as extreme or more extreme given HO is true (only in direction specified by HA) (α defined in 1 tail)P- value: what you get and greater2 tailed test:1 tailed
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