ecostats

Evaluating scientific evidence

Manu SaundersLeave a comment

In an era where PR rules the news and superlatives rule science, how can a reader really know what’s what?

Critical analysis skills are a key survival skill, but facts-on-demand has taken over in many modern educational structures. And despite the best intentions, the ‘openness’ of the internet has simply confused things. Opinions on scientific issues regularly rub shoulders with evidence and sometimes it can be hard to tell which is which (for scientists and non-scientists alike).

And what is ‘scientific evidence’ anyway? I wrote about this a few years ago, but it’s much more complex than I had room to explain.

I recently stumbled across this great series on how to evaluate scientific publications, from the German peer-reviewed medical magazine Deustches Ärtzeblatt. The papers are useful for teaching, for critical news audiences, and for practicing scientists. All articles are open access, translated from German. The series started in 2009 – I haven’t found a contents list or an apparent end-date for the series, so I will keep this updated as they get published. Continue reading →

Causal language in ecology papers

Manu Saunders13 Comments

‘Correlation does not imply causation’ is a statistical mantra. Most good high school and undergraduate statistics courses teach this, and most good science bloggers, journalists and scientists repeat it over and over again. But when and how far does that mantra extend into regression model territory? And what of the no-man’s-land surrounding this mysterious terra statistica?

Causal language refers to definitive statements that describe a cause and effect between two variables. It is in the same camp as the active voice, which is increasingly being promoted as the ‘way to write’ for scientists. Passive voice and non-directional language, once the standard of scientific writing, are now seen by some as vague, ambiguous and open to misinterpretation. But in our rush to be active, confident and ‘own’ our research results, are we risking misinterpretation and misunderstanding of science at the other end of the scale? “Building more roads increases bee abundance” might sound dramatic, convincing and galvanising…but it doesn’t mean quite the same thing as “Bee abundance was associated with the number of grassy road verges in the landscape”.* Continue reading →