Q: How do you interpret the p-value in Fisher's exact test?

The p-value indicates the probability of observing the data (or more extreme) under the null hypothesis of no association. A p-value < 0.05 typically indicates statistical significance, meaning there is evidence of an association between the variables. A p-value ≥ 0.05 suggests no significant association.

Q: What is the difference between Fisher's exact test and chi-square test?

Fisher's exact test gives exact p-values and is used for small samples, while the chi-square test gives approximate p-values and is used for larger samples. Fisher's test is more conservative and appropriate when expected frequencies are low, while chi-square is more powerful for larger samples.

Q: How do you calculate the odds ratio?

The odds ratio is calculated as (a × d) / (b × c) where a, b, c, d are the cells of the 2x2 contingency table. An odds ratio > 1 indicates a positive association, < 1 indicates a negative association, and = 1 indicates no association.

Q: What does the confidence interval for odds ratio tell us?

The 95% confidence interval for the odds ratio provides a range of plausible values for the true odds ratio. If the interval doesn't include 1, it suggests a significant association. If it includes 1, it suggests no significant association between the variables.

Q: What are the assumptions of Fisher's exact test?

Fisher's exact test assumes: 1) Independent observations, 2) Fixed marginal totals, 3) Binary categorical variables, 4) Random sampling, 5) No missing data. Unlike chi-square test, it doesn't require minimum expected frequencies.

Q: How do you report Fisher's exact test results?

Report: 1) The test name (Fisher's exact test), 2) The p-value, 3) The odds ratio and its confidence interval, 4) The contingency table, 5) The interpretation of results. Example: 'Fisher's exact test showed a significant association (p = 0.03, OR = 3.2, 95% CI: 1.1-9.4).'

Q: Can Fisher's exact test be used for larger tables?

Fisher's exact test is primarily designed for 2x2 tables. For larger contingency tables, you would typically use the chi-square test of independence or other appropriate tests. However, extensions exist for r×c tables, but they become computationally intensive.

Q: What are common applications of Fisher's exact test?

Common applications include: 1) Medical research (drug effectiveness, treatment outcomes), 2) Clinical trials (treatment vs. control groups), 3) Epidemiological studies (disease associations), 4) Quality control (defect rates), 5) Market research (preference studies), 6) Biological studies (genetic associations).

Question 1

What is Fisher's exact test?

Accepted Answer

Fisher's exact test is a statistical significance test used to determine if there is a non-random association between two categorical variables in a 2x2 contingency table. It's particularly useful when sample sizes are small and the chi-square test assumptions are not met.

Question 2

When should I use Fisher's exact test?

Accepted Answer

Use Fisher's exact test when: 1) You have a 2x2 contingency table, 2) Sample sizes are small (typically < 5 in any cell), 3) Expected frequencies are low, 4) The chi-square test assumptions are violated, 5) You need an exact p-value rather than an approximation.

Question 3

How do you interpret the p-value in Fisher's exact test?

Accepted Answer

The p-value indicates the probability of observing the data (or more extreme) under the null hypothesis of no association. A p-value < 0.05 typically indicates statistical significance, meaning there is evidence of an association between the variables. A p-value ≥ 0.05 suggests no significant association.

Question 4

What is the difference between Fisher's exact test and chi-square test?

Accepted Answer

Fisher's exact test gives exact p-values and is used for small samples, while the chi-square test gives approximate p-values and is used for larger samples. Fisher's test is more conservative and appropriate when expected frequencies are low, while chi-square is more powerful for larger samples.

Question 5

How do you calculate the odds ratio?

Accepted Answer

The odds ratio is calculated as (a × d) / (b × c) where a, b, c, d are the cells of the 2x2 contingency table. An odds ratio > 1 indicates a positive association, < 1 indicates a negative association, and = 1 indicates no association.

Question 6

What does the confidence interval for odds ratio tell us?

Accepted Answer

The 95% confidence interval for the odds ratio provides a range of plausible values for the true odds ratio. If the interval doesn't include 1, it suggests a significant association. If it includes 1, it suggests no significant association between the variables.

Question 7

What are the assumptions of Fisher's exact test?

Accepted Answer

Fisher's exact test assumes: 1) Independent observations, 2) Fixed marginal totals, 3) Binary categorical variables, 4) Random sampling, 5) No missing data. Unlike chi-square test, it doesn't require minimum expected frequencies.

Question 8

How do you report Fisher's exact test results?

Accepted Answer

Report: 1) The test name (Fisher's exact test), 2) The p-value, 3) The odds ratio and its confidence interval, 4) The contingency table, 5) The interpretation of results. Example: 'Fisher's exact test showed a significant association (p = 0.03, OR = 3.2, 95% CI: 1.1-9.4).'

Question 9

Can Fisher's exact test be used for larger tables?

Accepted Answer

Fisher's exact test is primarily designed for 2x2 tables. For larger contingency tables, you would typically use the chi-square test of independence or other appropriate tests. However, extensions exist for r×c tables, but they become computationally intensive.

Question 10

What are common applications of Fisher's exact test?

Accepted Answer

Common applications include: 1) Medical research (drug effectiveness, treatment outcomes), 2) Clinical trials (treatment vs. control groups), 3) Epidemiological studies (disease associations), 4) Quality control (defect rates), 5) Market research (preference studies), 6) Biological studies (genetic associations).

Fisher's Exact Test Calculator - Statistical Analysis for 2x2 Contingency Tables

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