When Studies Are in Error: Basic Statistical Vocabulary Needed to Understand Clinical Studies
Martin A . Weinstock
Background: Accurate understanding of certain basic statistical terms and principles is key to critical appraisal of published literature.
Objective: This review describes type I error, type II error, null hypothesis, p value, statistical significance, alpha, two-tailed and one-tailed test, effect size, alternate hypothesis, statistical power, beta, publication bias, confidence interval, standard error, and standard deviation, while including examples from reports of dermatologic studies.
Conclusion: The application of the results of published studies to individual patients should be informed by an understanding of certain basic statistical concepts.
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JCMS 1(1) Contents