OSU BUSMGT 2320 - s_7_One-way ANOVA Part I Autumn 2014 (38 pages)

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s_7_One-way ANOVA Part I Autumn 2014



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s_7_One-way ANOVA Part I Autumn 2014

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Pages:
38
School:
Ohio State University
Course:
Busmgt 2320 - Decision Sciences: Statistical Techniques

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Lecture 7 One Way ANalysis Of Variance ANOVA Part I What is the variation trying to tell us about a process about the people in the process W Edwards Deming 1900 1993 Learning Objectives 1 Understand how the analysis of variance procedure can be used to determine if the means from two or more populations are equal 2 Know how to calculate the sums of squares and mean squares in the one way ANOVA 3 Know how to determine the degrees of freedom for the different sources of variation in the One way ANOVA 4 Know the assumptions that form the basis of the ANOVA procedure 5 Understand the use of the F Distribution in performing the ANOVA Terminology ANOVA Family Significance Level Response Variable Dependent Variable Factor Independent Variable Treatment Experimental Unit CRD Total Variation Between Variation Within Variation Pooled Variance Estimate F ratio Post Hoc Analysis Sum of Squares Mean Squares Degrees of Freedom Aside if only random variance is present MINI CASE PACKAGE DESIGN SELECTION New Product Marketing Problem A marketing manager is interested in the effect of different types of packaging on the sales of a particular new item Three different types of packaging have been suggested for the item Will average sales be the same for all three package types The manager selects 15 stores from the population of stores that would stock the item The 3 package types are then randomly assigned to the stores 5 stores per package type The sales of the item at each of the stores are carefully recorded for a period of one month The Sales Data by Design i j 1 2 3 4 ni 5 Design 1 Design 2 Design 3 52 48 43 50 43 28 35 34 32 34 15 14 23 21 14 x1 47 2 s12 16 7 x2 32 6 s 22 7 8 x3 17 4 s32 18 3 Terminology Response Variable Factor Treatments Experimental Units 9 ONE WAY ANALYSIS OF VARIANCE in a nutshell Comparing multiple 2 or more population means H0 1 2 I Ha Not all i are equal Required Conditions 1 Independent 2 The treatment populations are distributed Use Q Q Normal plots



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