When researchers test for statistical significance, they compare different sets of values - such as bladder infections before and bladder infections after using a medication - while taking into account how many people participated in the research, how dramatic their findings seem to be, and what some of the characteristics were of the people they compared. They then use complicated mathematical formulas to calculate probability values. For our bladder infection drug, this probability value will tell us how likely it is that people in the study got better because the drug did its job, or whether they got better simply because of chance or due to some other unknown factor other than the drug. If the researcher finds that the probability value is low (usually less than 5%, 1% or even 1/10th of 1%), he or she can conclude that the drug really does work. These probability values - called p values - represent percentages, but are typically represented as p<.05, p<.01, or p<.001, or more specifically, as p=.023, p=.0067. For example, p<.01 means that there is a less than 1% chance that our bladder medication seemed to work because of chance alone. If probabilities are low, researchers describe them as statistically significant. These are key words you should look for as you read. Remember: the lower the p value, the smaller the percentage, the greater the significance and the less likely that something happened just because of chance.