Hypothesis testing: means.

In most biomedical research, investigators hypothesize about the relationships of various factors, collect data to test those relationships, and try to draw conclusions about those relationships from the data collected. In many cases, investigators test relationships by comparing the average level of a factor between 2 groups or between 1 group and a standard reference. This framework is as true for understanding the basic role of cardiac myosin binding protein-C phosphorylation in cardiac physiology1 as it is for evaluating non–high-density lipoprotein cholesterol (HDL-C) as a predictor of myocardial infarction in large groups of individuals.2 In this article we describe hypothesis testing, which is the process of drawing conclusions on the basis of statistical testing of collected data, and the specific approach used to test means (or average levels of a collected data element). These concepts are covered in detail in many statistical textbooks at various levels, including Pagano and Gauvreau,3 Zar,4 and Kleinbaum et al.5