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(Circulation. 2006;114:1078-1082.)
© 2006 American Heart Association, Inc.

Statistical Primer for Cardiovascular Research

Hypothesis Testing

Means

Roger B. Davis, ScD; Kenneth J. Mukamal, MD, MPH

From the Division of General Medicine and Primary Care, Beth Israel Deaconess Medical Center, Boston, Mass.

Correspondence to Roger B. Davis, ScD, Division of General Medicine and Primary Care, Beth Israel Deaconess Medical Center, 330 Brookline Ave, RO-108, Boston, MA 02215. E-mail rdavis@bidmc.harvard.edu

An extract of the first 250 words of the full text is provided, because this article has no abstract.

	Introduction

 
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

	Hypothesis Testing

 
The purpose of statistical inference is to draw conclusions about a population on the basis of data obtained from a sample of that population. Hypothesis testing is the process used to evaluate the strength of evidence from the sample and provides a framework for making determinations related to the population, ie, it provides a method for understanding how reliably one can extrapolate observed findings in a sample under study to the larger population from which the sample was drawn. The investigator formulates a specific hypothesis, evaluates data from the sample, and uses these data to . . . [Full Text of this Article]

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