Tools

Fisher's exact test

Calculator

  Group 1 Group 2  
Observation A  
Observation B  
Tail / side

Result


Fill in the fields in the calculator box and press 'Calculate' for the statistical significance.

Calculator

  Group 1 Group 2  
Observation A  
Observation B  
Observation C  
Tail / side

Result


Fill in the fields in the calculator box and press 'Calculate' for the statistical significance.

Calculator

  Group 1 Group 2  
Observation A  
Observation B  
Observation C  
Observation D  
Tail / side

Result


Fill in the fields in the calculator box and press 'Calculate' for the statistical significance.

Calculator

  Group 1 Group 2 Group 3
Observation A
Observation B
Observation C
Tail / side

Result


Fill in the fields in the calculator box and press 'Calculate' for the statistical significance.

Calculator

Tail / side

Upload a tab delimited text file containing multiple contingency tables. Example:

UID C1R1 C1R2 C1R3 C2R1 C2R2 C2R3
1 15 3 4 7 1 14
2 8 1 3 3 9 13
3 7 3 6 2 4 9

Where UID stands for Unique ID, C for Column, and R for Row. UID has to be in sequential order as well as the column and row indices.

Result


Information

Fisher's exact test is a statistical test that can be used to calculate whether there is a significant association between categorical variables. It permits calculation of precise probabilities in situation where sample sizes are small so the normal approximation and chi-square calculations are liable to be inaccurate. Ronald Fisher, the inventor of the test, published the test in 1941 where its first uses were for 2x2 contingency tables.