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(Circulation. 2006;114:1545-1548.)
© 2006 American Heart Association, Inc.

Statistical Primer for Cardiovascular Research

Hypothesis Testing

Proportions

Kimberlee Gauvreau, ScD

From the Department of Cardiology, Children’s Hospital, Boston, Mass.

Correspondence to Kimberlee Gauvreau, ScD, Department of Cardiology, Children’s Hospital, 300 Longwood Ave, Boston, MA 02115. E-mail gauvreau@tch.harvard.edu

Key Words: statistics • hypothesis testing

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

	Introduction

 
The process of drawing conclusions about an entire population on the basis of the information contained in a random sample drawn from that population is known as statistical inference. Methods of statistical inference fall into 2 general categories: estimation and hypothesis testing. With estimation, our goal is to describe or estimate some characteristic of a population of interest, such as the mean pulmonary regurgitation fraction of all patients alive 10 years after repair of tetralogy of Fallot or the proportion of children with acute Kawasaki disease who develop coronary artery abnormalities. With hypothesis testing, we begin by claiming that the population parameter of interest is equal to some postulated value (or, in the situation in which we are comparing 2 populations, that the 2 parameters are equal to each other). This statement about the value of the population parameter is called the null hypothesis (H₀). The alternative hypothesis (H_A) is a second statement that contradicts the null. Together, the null and alternative hypotheses account for all possible values of the population parameter; consequently, 1 of the 2 statements must be true. After formulating the hypotheses needed to answer our study question, we draw a random sample from the population of interest and use the information in this sample to calculate a test statistic. The test statistic is compared with the critical values of an appropriate probability distribution. If there is evidence that the sample could not have come from a population with the postulated value of the parameter, . . . [Full Text of this Article]

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