CAMBRIDGE, Mass. — SCIENTISTS have often been accused of exaggerating the threat of climate change, but it’s becoming increasingly clear that they ought to be more emphatic about the risk. The year just concluded is about to be declared the hottest one on record, and across the globe climate change is happening faster than scientists predicted.

Science is conservative, and new claims of knowledge are greeted with high degrees of skepticism. When Copernicus said the Earth orbited the sun, when Wegener said the continents drifted, and when Darwin said species evolved by natural selection, the burden of proof was on them to show that it was so. In the 18th and 19th centuries, this conservatism generally took the form of a demand for a large amount of evidence; in the 20th century, it took on the form of a demand for statistical significance.

We’ve all heard the slogan “correlation is not causation,” but that’s a misleading way to think about the issue. It would be better to say that correlation is not necessarily causation, because we need to rule out the possibility that we are just observing a coincidence. Typically, scientists apply a 95 percent confidence limit, meaning that they will accept a causal claim only if they can show that the odds of the relationship’s occurring by chance are no more than one in 20. But it also means that if there’s more than even a scant 5 percent possibility that an event occurred by chance, scientists will reject the causal claim. It’s like not gambling in Las Vegas even though you had a nearly 95 percent chance of winning.

Where does this severe standard come from? The 95 percent confidence level is generally credited to the British statistician R. A. Fisher, who was interested in the problem of how to be sure an observed effect of an experiment was not just the result of chance. While there have been enormous arguments among statisticians about what a 95 percent confidence level really means, working scientists routinely use it.