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. | ||
| + | |||
| + | ==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. | ||
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.