Too often, scientists today rely on statistics that they don’t understand. As a result, “there are more false claims made in medical literature than anyone appreciates,” biostatistician Steven Goodman told Science News. In fact, the entire system of how scientists use statistics to draw conclusions is being called into question. Science News quotes statistician David Salsburg who wrote, “This problem is still unsolved, and… if it remains unsolved, the whole of the statistical approach to science may come crashing down on its own inconsistencies.”
Science News explains the problem:
It’s science’s dirtiest secret: The “scientific method” of testing hypotheses by statistical analysis stands on a flimsy foundation. Statistical tests are supposed to guide scientists in judging whether an experimental result reflects some real effect or is merely a random fluke, but the standard methods mix mutually inconsistent philosophies and offer no meaningful basis for making such decisions. Even when performed correctly, statistical tests are widely misunderstood and frequently misinterpreted. As a result, countless conclusions in the scientific literature are erroneous, and tests of medical dangers or treatments are often contradictory and confusing.
Source: Science News
