• The level at which statistical significance occurs from a finding.
• It reflects the strength of the results found in a study and determines the likelihood that the results were due to chance.

• A p-value of < 0.05 simply means that the probability the results were due to chance or random error is < 1 in 20 or < 5%.
• The smaller the p-value, the lower the likelihood the results found in a study were due to chance or random error - or - said another way, "the smaller the p-value the more likely the results found from a study are real"
• This is why researchers hope or desire to have small p-values
• It is important to know that the p-value does NOT tell you anything about the:
• Clinical significance of the findings
• Size of the effect found

• If a study was completed and found that the two interventions being evaluated were statistically different and reported a p-value of 0.01, then we can say that there is a 1% chance that those results found in this study are either due to chance or random error.
  
• It is important to remember these two things:
• The lower the p-value the lower the likelihood of the results occurring from chance.
  
• The p-value does not tell you anything about the clinical significance of those results - that is for clinicians to decide for themselves. 
  

• Power (1 - β)
• Alpha (α) Value
• Beta (β)
  

Editors: 

• Anthony J. Busti, MD, PharmD, FNLA, FAHA
• Karolina DeAugustinis, MD
• Dylan Kellogg, MD
  

Last Reviewed: July 2015