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Purdue - IE 33000 - Study Guide - Final

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Purdue - IE 33000 - Study Guide - Final

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School: Purdue University
Department: Industrial Engineering
Course: Probability and Statistics in Engineering II
Professor: Tba
Term: Fall 2015
Tags:
Name: IE 330 - Exam 3 Study Guide
Description: Study Materials
Uploaded: 04/14/2018
2 Pages 75 Views 60 Unlocks
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Unformatted text preview: < Exam 3 Study Guide Friday, April 13, 2018 10:56 PM Exam Info Covers chapters 13 ond 14 Will be IN CLASS on April 16th, 2017 at 8:30am * 8 qursti on s, 4.5 of which will be T/F (4 p ) * 50 min to complere * NO CALCULATORS Practice from 2017 will be the biggest help . Most of the com will be interpreting results forker thor doing calca lations Equatlons: None Key Concepts One - Factor ANOVA. - Interpretation A one foctor analysis of variance showed that the effect of factor was Statisfically significant (F8,3) Lot, P0.001). ) b. do this is value is C r .0 Posr hoc analysis using fukey simultaneous comparisons indicared that the responses & lees vers ( , s .) and C ( 20 7,50 at higher than a level B1A , 0.15) - From results be able to find o whom the factors how many levels and whor Hey at how many observations per level - Factor's levels. c treonents Cone-factor CWLY) Experiment Design - Calculare # of observations lelini Tat) - Goruntee koudoni Battan - know how you will test results be foetle experiment - Factors - Independant variable s - Responses : Depeudour variables Same member of replicarias per treurer = Balanced 'replicat lens # of times each preostment is executed - Confound : sa vivielle an accounted forMuldi - Foctor ANOVA - Con hove multiple factors (2+) each factor has multiple levels - Assumptlon s "Requirements response = normally disz. * Con stone varriance across levels of factors observations must be IID distinguish the efect of one factor from orders o distinguish de efect experimental Sochors from non - exprimansa/ Sacs ors - Plain Effects factor checs s response - Interactions factor effects factor's Meer om response - Fractlanal Factorial 2' 24" - less runs, less interperable data

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