lecture11 - Psych 100A Winter 2010 Lecture Lecture 11:...

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Psych 100A Winter 2010 ecture 1: Power Analysis & Lecture 11: Power Analysis & Statistical Inference (cont.) 1. Relationships among , power and n 2. Power curves 3. Confidence intervals for when 2 is unknown 4. Properties of the t-distribution inding areas in istribution 5. Finding areas in t-distribution 1
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Power – Probability of rejecting null hypothesis when a specified alternative hypothesis is true. Power = Area under the alternative distribution curve’s tail. If the alternative distribution mean is less than the null distribution mean then it is the left tail. 2
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Directional z-test 3
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2. Power curves The power of a test is the probably of rejecting the null hypothesis given that the alternative hypothesis is true. Power depends on 1. Type of test: H 0 versus one- or two-sided H A 2. Sample size: n eaningful difference: 3. Meaningful difference: = | 0   A | 4. Type I error: -level tandard deviation: 5. Standard deviation: [You can combine 3 & 5 to get effect size | 0 A |/ ] Power curves show relationships among power and parameters when one is varied and others are fixed. 7
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Example, flex-time study: Compute power when varies from 0.1 to 3 days in a one-sided test of H A : < 6.3 days. Fixed: H O : = 6.3 , = 0.05 , = 3 , n = 100 . | 0  A | = A % Power 1  100 0.1 0.2 6.2 6.1 16 9 60 80 Power 0.5 1.0 1 5.8 5.3 2 51 95 8 40 Percent 1.1 1.2 1.5 5.2 5.1 4.8 99 99.96 98 0 20 3.0 3.3 99.999 34567 Alternative Means 8
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Flex-time study continued: ixed: ±63± 0 05 3 n = 100 Fixed: H O : = 6.3, = 0.05 , = 3, n = 100.
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This note was uploaded on 03/15/2010 for the course PSYCHOLOGY 100B taught by Professor Firstenberg,i. during the Winter '10 term at UCLA.

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lecture11 - Psych 100A Winter 2010 Lecture Lecture 11:...

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