Even when a particular direction of treatment effect can be predicted a two-tailed test is still often used. The goal of hypothesis testing is usually to correctly reject the null hypothesis, or in other words, to show that the treatment applied has had an effect. The probability of correctly rejecting the null hypothesis is called the power of a statistical test. Statistical power is large when the treatment effect is large. Put another way, you are more likely to correctly reject the null hypothesis when the treatment has created a large difference between your sample data and the original population.
Statistical power is greater for one-tailed tests.
Larger samples provide greater power. Finally, read the summary on pp. This is a personal page published by the author. The ideas and information expressed on it have not been approved or authorised by Monash University either explicitly or impliedly. In no event shall Monash University be liable for any damages whatsoever resulting from any action arising in connection with the use of this information or its publication, including any action for infringement of copyright or defamation.