Learn to Read a Scientific Report

Causation vs. correlation
How do you know if a study’s results answer the question it set out to ask? Sometimes an outcome is just a coincidence—there’s a correlation but no causation. Meta-analyses pool the results of smaller studies and filter signal from that kind of noise. 

True size of the effect
Watch out for weasely language—a “threefold increase” might only be a shift from 1 percent to 3 percent. One recent paper reported that women’s mortality risk rose 133 percent. That sounds scary, but the elevated mortality rate was still just 1.9 percent. 

Statistical power
Look at two key factors, the n and the p. The n is the number of subjects used in the study. Multifaceted experiments typically have fewer subjects than simple surveys. Genetics studies need a big n. The p value lets you know whether the result is “statistically significant”—it’s the probability of something occurring by chance alone. You want to see a p of less than 0.05. (Results can be statistically significant and still only show correlation, or have confounding factors.) 

Conflicts of interest
Most journals now note this as a matter of policy. Was the company making the drug or product associated with the laboratory that did the study? Are any of the authors trying to sell a product? For example, the authors of a study exploring the effectiveness of “brain training” techniques on cognitive enhancement worked for the company that developed (and sold) those techniques. They disclosed this, but that’s still a red flag.

http://www.wired.com/wiredscience/2012/10/mf-learn-to-read-a-scientific-report/