UT Knoxville STAT 201 - Chapter 26 (34 pages)

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Chapter 26



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Chapter 26

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Pages:
34
School:
University of Tennessee
Course:
Stat 201 - Introduction to Statistics
Introduction to Statistics Documents

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Chapter 26 Chapter26 Presentation 1213 Comparing Counts Copyright 2009 Pearson Education Inc 1 Test of Independence Contingency tables categorize counts on two categorical variables so that we can see whether the distribution of counts on one variable is contingent on the other A test of independence examines whether there is a significant association between a pair of categorical variables Chapter26 Presentation 1213 Copyright 2009 Pearson Education Inc 2 Test of Independence Cont In Chapter 3 we saw an example of survival on board the Titanic Was survival proportion associated with the passengers ticket class Chapter26 Presentation 1213 Copyright 2009 Pearson Education Inc 3 Test of Independence Cont In a test of independence of two categorical variables the generic hypotheses are H0 Row and column classifications are independent HA Row and column classifications are not independent i e they are associated with each other Chapter26 Presentation 1213 Copyright 2009 Pearson Education Inc 4 Assumptions and Conditions Counted Data Condition Check that the data are counts for the categories of a categorical variable Independence Assumption The counts in the cells should be independent of each other Randomization Condition The counts should be a random sample from some population 10 Condition The sample should consist of less than 10 of the population of interest Question does the Titanic data meet the two condition above Chapter26 Presentation 1213 Copyright 2009 Pearson Education Inc 5 Assumptions and Conditions cont Sample Size Assumption We must have enough data for the methods to work Expected Cell Frequency Condition We should expect to see at least 5 individuals in each cell Chapter26 Presentation 1213 Copyright 2009 Pearson Education Inc 6 What Is Meant by Expected Cell Count Given the row totals and column totals in the contingency table what cell counts would we expect to see inside the table if the row and column classifications were independent of each other



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