Unformatted text preview: very likely use different words, so look at these as examples: Example 2 The outcomes are the same The outcomes are not the same Example 3 Rounds played is the same each day Rounds played is not the same each day Example 4 There is no difference in the proportions There is a difference in the proportions Example 5 The proportions are the same The proportions are not the same And so on. Here is the key to recognize chisquare: we recognize a chisquare application by seeing that we are given several categories each with observed frequencies, and are asked if the expected frequencies fit those categories. (Note: in this course we will only study the "equal expected frequencies" and not include the "unequal expected frequencies"). BTW  we also know that chisquare is typically nominal data. ...the level of measurement that relates to categories. And we must use degrees of freedom with this data (use the ChiSquare Critical Values, Appendix E)....
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This note was uploaded on 10/10/2010 for the course STATS Stats301 taught by Professor Regis during the Spring '10 term at DeVry Irvine.
 Spring '10
 Regis
 Statistics

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