# Articles on One-Sided Statistical Tests

Articles on one-sided significance tests and confidence intervals. Learn what is a one-tailed test, when it is required in practical and theoretical research.

- One-sided statistical tests are just as accurate as two-sided tests
- The paradox of one-sided vs. two-sided tests of significance
- Directional claims require directional statistical hypotheses
- A p-value is meaningless without a specified null hypothesis
- When is a one-sided hypothesis required?
- 12 myths about one-tailed vs. two-tailed tests of significance
- Examples of improper use of two-sided hypotheses
- Fisher, Neyman & Pearson - advocates for one-sided tests and confidence intervals
- Proponents of one-sided statistical tests
- Examples of negative portrayals of one-sided significance tests
- Is the widespread usage of two-sided tests a result of a usability issue?
- Reasons for misunderstanding and misapplication of one-sided tests
- Refining statistical guidelines and requirements for one-sided tests
- The hidden costs of bad statistics in clinical research