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Chi-square Alternative Hypothesis Chi-square Null Hypothesis
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No matter what you have in rows and columns, there’s no correlation (i.e. all regions have the same preferences). At least one region differs from the rest.
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Observed Frequency (f O ) Chi-square Null Hypothesis
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i.e. no relationship between gender and colors they purchase (males and females have the same color preference) Data obtained from the survey.
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- Row Total Column TotalOverall sample size Expected Frequency (f e )
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Number you’d expect if the null hypothesis were true. Equation for expected frequency (f e ):
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Observed and Expected Frequency n
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Overall sample size. For chi-square analysis, the sum of ____ and the sum of ____ have to be the same.
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P-value = 0 Exceeds
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If the chi-square test statistic ____ the critical value, reject the null hypothesis. Reject the null hypothesis at any confidence level.
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Chi-square Alternative Hypothesis Chi-square Null Hypothesis
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i.e. you’re not sex discriminating because there’s no relationship between sex and hiring i.e. you’re engaged in sex discrimination
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Yates Correction Factor Yates
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Had a problem with test statistics when degrees of freedom equal one; only 75% agreement among statisticians. Subtract 50% before proceeding with chi- square analysis if the degrees of freedom equal one; always reduces the test statistic.
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Contingency Table Non-Parametric Test
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Non-formal hypothesis testing (ranking). A table set up to compare hypotheses concerning the headings in the rows and the columns.
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Expected Frequency (f E ) Observed Frequency (f O )
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Frequencies observed from sample information; usually given in problems which students must work. The frequencies which would be expected if there is no relationship between rows and columns of data.
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Yates’ Correction Factor Chi-Square Test Statistic
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A test statistic that compares observed and expected frequencies to determine if a relationship exists between them. A correction process that adjusts the chi- square test statistic when there is a single degree of freedom.
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Sign Test Non-Parametric Test
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Using test statistics that do not involve stringent assumptions concerning the parent population. Used in sports like boxing, where you use a 10-point must.
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Sign Test Alternative Hypothesis Sign Test Null Hypothesis
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50% of the data is positive and 50% of the data is negative (the fight is a draw). i.e. somebody wins the boxing fight because the population proportion does not equal zero
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Sampling Error Ties
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Disregarded in sign tests. i.e. caused because it depends where you sit in a boxing match – your perspective differs
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Coefficient of Rank Correlation +1, -1, 0
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rank correlation, ____ ranks exactly the same as the other person, ____ ranks exactly the opposite, and ____ is not correlated at all. i.e. used in dating sites
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This note was uploaded on 09/08/2011 for the course ECO 3411 taught by Professor Staff during the Fall '08 term at University of Central Florida.

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