Fisher's exact test

Fisher's exact test

Study interpretation and drawing conclusions from data

Bias, confounding, and threats to validity

Bias in interpreting results of clinical studies
Bias in performing clinical studies
Confounding
Information bias
Interaction
Selection bias

Causation

Disease causality

Chance

Hypothesis testing: One-tailed and two-tailed tests
Chi-squared test
Fisher's exact test
Kappa coefficient
Mann-Whitney U test
Spearman's rank correlation coefficient
One-way ANOVA
Paired t-test
Repeated measures ANOVA
Two-sample t-test
Two-way ANOVA
Type I and type II errors

Key Takeaways

Fisher's exact test is a statistical test that uses a 2x2 categorical data design. It is used to determine whether the proportions of two categorical variables are different from each other. It is a more powerful alternative to the chi-squared test, and is particularly useful when there are small sample sizes.