P Values

  • Jørn Olsen
  • Kaare Christensen
  • Jeff Murray
  • Anders Ekbom
Chapter
Part of the Springer Series on Epidemiology and Public Health book series (SSEH, volume 1)

Abstract

In the past, much emphasis was put on the so-called significance testing. The investigator assumed a null hypothesis stating no association between the exposure and the disease (usually the real hypothesis would be the opposite of the null hypothesis). Then he/she would calculate a P value. The P value would indicate the probability of getting the data he/she found or data that were even further away from the null hypothesis (the no-effect value), given the null hypothesis was true (and other conditions). If this P value was below a given level (often < 0.05) it was said that the finding was statistically significant and the null hypothesis was rejected as a likely explanation of the data.

Copyright information

© Springer Science+Business Media, LLC 2010

Authors and Affiliations

  • Jørn Olsen
    • 1
  • Kaare Christensen
    • 2
  • Jeff Murray
    • 3
  • Anders Ekbom
    • 4
  1. 1.School of Public HealthUniversity of California, Los AngelesLos AngelesUSA
  2. 2.Institute of Public HealthUniversity of Southern DenmarkOdense CDenmark
  3. 3.Department of Pediatrics, 2182 MedLabsUniversity of IowaIowa CityUSA
  4. 4.Department of MedicineKarolinska InstitutetStockholmSweden

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