statistics

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 →

Data, not just for scientists

Manu Saunders7 Comments

Early last year I wrote a post on ecology and mathematics that was inspired by an online discussion happening at the time. Although comprehensive advanced maths skills are not essential to being an influential or inspiring ecologist, a good level of mathematical knowledge and understanding of statistical analysis is definitely necessary to create honest science and communicate the importance of your work to others.

But it’s not just ecologists who need mathematical common sense. Anyone who deals with, or is interested in science needs to understand the ambiguity of an average, or the difference between a regression and a correlation. In fact, anyone who cares about the society they live in should be aware how deeply statistics and data now influence the way we live – policies and decisions on anything from what product choices you find in retail stores to how much tax you pay are all based on data.

Why does this matter to us? Well, if those data are a bit dodgy, or haven’t been analysed and presented appropriately, problems arise. And when these kinds of data misrepresentations are used to fuel public opinion or inform government policy, there can be serious impacts on communities, individuals and ecosystems. Continue reading →

Ecology vs Math: do we need to pick sides?

Manu Saunders33 Comments

Like many other young ecologists, I chose this career because I cared about the Earth and because I wanted a job that gave me the thrill of discovery every day. Whether it’s seeing a new ecosystem for the first time, sighting a wild plant or animal species I’ve never seen before, coming up with a novel theory, methodology, or sampling technique, or finally ‘getting’ the statistical analysis I’ve been struggling with for weeks – I get to play explorer every day, and I love it.

Sadly, in some countries, it is a field that struggles to convince a large number of graduates to stay in a research career. This is mostly because of funding issues, but can also come from confusion after 4-5 years of being pushed and pulled between too many stimulating sub-disciplines and inspiring mentors.

Many students are bombarded throughout their degree with promotion of multiple sub-disciplines of ecology as “the one that rules them all”. As a naive undergraduate with a lot to learn about the industry and the world in general, this can influence which career path they take.

So it’s heartening when the more experienced generation encourage aspiring scientists to follow their passion and intuition and stick with science (particularly ecology and the natural sciences), even if they don’t fit into the apparent intellectual “norms”. E.O. Wilson’s recent piece in The Wall Street Journal is just that. Continue reading →