For most of us, “significant” means important; in statistics it means probably true (not due to chance) but not necessarily important. In particular, significance levels in statistics show how likely a result is due to chance. The most common level—one thought to make it good enough to believe—is 0.95, which means the finding has a 95 percent chance of being true.

This can also be misleading, however. No statistical report will indicate a 95 percent, or 0.95, in its answer, but it will show the number 0.05. Thus, statisticians say the results in a “backward” manner: they say that a finding has a 5 percent chance of not being true. To find the significance level, all one has to do is subtract the number shown from 1. For example, a value of 0.05 means that there is a 95 percent (1 - .05 5 0.95) chance of it being true; for a value of 0.01, there is a 99 percent chance (1 - 0.01 5 0.99) of it being true; and so on.