ANOVA for Dependent Populations-ECO6416

# ANOVA for Dependent Populations-ECO6416 - The ANOVA Table...

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ANOVA for Dependent Populations Populations can be dependent in either of the following ways: 1. Every subject is tested in every experimental condition. This kind of dependency is called the repeated-measurement design. 2. Subjects under different experimental conditions are related in some manner. This kind of dependency is called matched-subject designed. An Application: Suppose we are interested in studying the effect of alcohol on driving ability. Ten subjects are given three different alcohol levels and the number of driving errors are tabulated below: Mean 0 oz 2 3 1 3 1 4 1 3 2 1 2.1 2 oz 3 2 1 4 2 3 1 5 1 2 2.4 4 oz 3 1 2 4 2 5 2 4 3 2 3.1 The test null hypothesis is: H 0 : µ1 = µ2 = µ3, and the alternative: H a : at least two of the means are not equal. Using the ANOVA for Dependent Populations JavaScripts, we obtain the needed information in constructing the following ANOVA table:
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Unformatted text preview: The ANOVA Table Sources of Variation Sum of Squares Degrees of Freedom Mean Squares F-Statistic Subjects 31.50 9 3.50-Between 5.26 2 2.63 7.03 Within 6.70 18 0.37 Total 43.46 29 Conclusion: The p-value is P= 0.006, indicating a strong evidence against the null hypothesis. The means of the populations are not equal. Here, one may conclude that person who has consumed more than certain level of alcohol commits more driving errors. A “block design sampling" implies studying more than two dependent populations. For testing the equality of means of more than two populations based on block design sampling, you may use Two-Way ANOVA Test . In the case of having block design data with replications, use Two-Way ANOVA with Replications to obtain the needed information for constructing the ANOVA tables....
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## This note was uploaded on 10/05/2011 for the course ECO 6416 taught by Professor Staff during the Spring '08 term at University of Central Florida.

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