Difference between revisions of "Fisher's Exact Test"

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(Created page with "<div style="font-size:25px">'''FISHERSEXACTTEST(DataRange,NewTableFlag)'''</div><br/> *<math>DataRange</math> is the array of x and y values. *<math>NewTableFlag</math> is eit...")
 
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*<math>DataRange</math> is the array of x and y values.
 
*<math>DataRange</math> is the array of x and y values.
 
*<math>NewTableFlag</math> is either TRUE or FALSE. TRUE for getting results in a new cube. FALSE will display results in the same cube.
 
*<math>NewTableFlag</math> is either TRUE or FALSE. TRUE for getting results in a new cube. FALSE will display results in the same cube.
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 +
==Description==
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* This function gives the test statistic of the Fisher's Exact Test.
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* Since this method is more computationally intense, it is best used for smaller samples.
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* Like the chi-square test for (2x2) tables, Fisher's exact test examines the relation between two dimensions of the table (classification into rows vs. columns).
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* For experiments with small numbers of participants (below 1,000), Fisher’s is more accurate than the chi-square test or G-test.
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* The null hypothesis is that these two classifications are not different.
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* The P values in this test are computed by considering all possible tables that could give the row and column totals observed.

Revision as of 08:55, 27 February 2018

FISHERSEXACTTEST(DataRange,NewTableFlag)


  • is the array of x and y values.
  • is either TRUE or FALSE. TRUE for getting results in a new cube. FALSE will display results in the same cube.

Description

  • This function gives the test statistic of the Fisher's Exact Test.
  • Since this method is more computationally intense, it is best used for smaller samples.
  • Like the chi-square test for (2x2) tables, Fisher's exact test examines the relation between two dimensions of the table (classification into rows vs. columns).
  • For experiments with small numbers of participants (below 1,000), Fisher’s is more accurate than the chi-square test or G-test.
  • The null hypothesis is that these two classifications are not different.
  • The P values in this test are computed by considering all possible tables that could give the row and column totals observed.