Every clinical trial should be planned. This plan should include the objective of trial, primary and secondary end-point, method of collecting data, sample to be included, sample size with scientific justification, method of handling data, statistical methods and assumptions. This plan is termed as clinical trial protocol. One of the key aspects of this protocol is sample size estimation. The aim of this article is to discuss how important sample size estimation is for a clinical trial, and also to understand the effects of sample size over- estimation or under-estimation on outcome of a trial. Also an attempt is made to understand importance of minimum sample to detect a clinically important difference. This article is also an attempt to provide inputs on different parameters that impact sample size and basic rules for these parameters with the help of some simple examples.
Keywords: Sample size; Type I error; Type II error; clinically significant; power; statistically significant.