Hypothesis testing and statistical test selection: Fundamentals of statistics in clinical studies - part II

Abstract

Hypothesis testing is a systematic procedure for evaluating assumption about difference or relationship between variables. This process involves four main steps: formulating a hypothesis, establishing decision-making criteria, calculating statistical values, and drawing a conclusion. In clinical studies, the process begins with the formulation of a hypothesis, which includes both the alternative and null hypothesis. Statistical tests are employed to assess the null hypothesis by calculating key statistical values, such as the test statistic and p-value. Based on the p-value, conclusions are made regarding the presence of a significant difference or relationship between the variables under study. The selection of an appropriate statistical test depends on various factors, and understanding these factors is crucial for making valid inferences and accurately interpreting clinical study results. This professional article outlines the steps involved in hypothesis testing and discusses the key considerations for selecting the appropriate statistical test.