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Analysis of Variance Chapter 12 . McGraw-Hill/Irwin

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1 Analysis of Variance Chapter 12 . McGraw-Hill/Irwin
Copyright © 2012 by The McGraw-Hill Companies, Inc. All rights reserved.

2 Learning Objectives 1. List the characteristics of the F distribution. 2. Organize data into ANOVA tables for analysis. 3. Conduct a test of hypothesis among two or more treatment means and describe the results. 12-2

3 F-Distribution 1. There is a “family” of F Distributions. A particular member of the family is determined by two parameters: the degrees of freedom in the numerator (v1) and the degrees of freedom in the denominator (v2). 2. The F distribution is continuous 3. F value cannot be negative. 4 The F distribution is positively skewed. 12-3

4 One-Way ANOVA: Comparing Means of Two or More Populations
The F distribution is used for testing whether two or more population means are equal. If there are k populations, the numerator degrees of freedom is k – 1. If there are a total of n observations, the denominator degrees of freedom is n – k. Assumptions: The sampled populations follow the normal distribution. The populations have equal standard deviations. The samples are randomly selected and are independent. 12-4

5 One-Way ANOVA The hypotheses are H0: µ1 = µ2 =…= µk
The Test Statistic F follows F distribution and can be calculated as. The Decision rule Reject the null hypothesis if F > F,k-1,n-k H0: µ1 = µ2 =…= µk H1: The means are not all equal 12-5

6 One-Way ANOVA – Example
Recently a group of four major carriers joined in hiring Brunner Marketing Research, Inc., to survey recent passengers regarding their level of satisfaction with a recent flight. The survey included questions on ticketing, boarding, in-flight service, baggage handling, pilot communication, and so forth. Twenty-five questions offered a range of possible answers: excellent, good, fair, or poor. A response of excellent was given a score of 4, good a 3, fair a 2, and poor a 1. These responses were then totaled, so the total score was an indication of the satisfaction with the flight. Brunner Marketing Research, Inc., randomly selected and surveyed passengers from the four airlines. Northern WTA Pocono Branson Is there a difference in the mean satisfaction level among the four airlines? Use the .01 significance level. 12-6

7 One-Way ANOVA – Example
Step 1: State the null and alternate hypotheses. H0: µA = µD = µU = µUS H1: The means are not all equal Reject H0 if F > F,k-1,n-k Step 2: State the level of significance. The .01 significance level is stated in the problem. Step 3: Find the appropriate test statistic. Because we are comparing means of more than two groups, use the F test statistic 12-7

8 One-Way ANOVA – F test statistic
Treatment/factor: the criteria used to classify the populations. In this example, the treatment/factor is airlines. Total variation (SS) = Variation due to difference between treatments (SST) + Variation due to within treatments (SSE) SS = SST + SSE The test statistic is computed by: 12-8

9 One-Way ANOVA – F test statistic
where: is the sample mean for each treatment 12-9

10 One-Way ANOVA – F test statistic
Northern WTA Pocono Branson 12-10

11 One-Way ANOVA – F test statistic
American Delta United US Airways American Delta United US Airways American Delta United US Airways American Delta United US Airways 12-11

12 One-Way ANOVA – F test statistic

13 One-Way ANOVA – Example
Step 4: State the decision rule. Reject H0 if F > F,k-1,n-k F > F.01,4-1,22-4 F > F.01,3,18 F > 5.09 Step 5: Make a decision The computed value of F is 8.99, which is greater than the critical value of 5.09, so the null hypothesis is rejected. Conclusion: The population means are not all equal. The mean scores are not the same for the four airlines; at this point we can only conclude there is a difference in the treatment means. We cannot determine which treatment groups differ or how many treatment groups differ. 12-13

14 One-Way ANOVA – Excel See textbook, P 452, #2 for more detials.
We can also use the p-value to for the hypothesis test. Recall that the null hypothesis is rejected when p-value < α. Here p-value = .0007, which is less than .05. Thus H0 is rejected. Data Airlines 12-14

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