How To Teach Me Statistics

A few weeks ago I was swearing at my computer and had to go buy a Twix bar from the canteen to calm myself. There was some frantic chocolate scoffing that afternoon.

The source of my irritation? Statistics. I am not a great wielder of statistical power, but I am very interested in their dark arts. This leads to the common situation where I know I’m doing something wrong, such as using stepwise regressions to build a model, the fact I use frequentist over Bayesian probabilities, and even my over reliance on P Values to communicate scientific results, but I just don’t know how to do it better.

I’m expecting there are three reactions to that sentence. The first is “I don’t have a clue what any of that means”. Don’t worry, my grasp of it is very shaky, and it’s not something I’ve ever been taught. It’s something I’ve discovered through hanging out with statisticians.

The second is “Man, I have that exact same problem, but every time I try and learn how to do it, I can’t figure it out.” My friends we are in the same boat. I do not feel I have enough statistical training to tackle these problems.

And lastly the third kind of person is reading that and thinking “Well obviously the answer is *string of gibberish*”

I have had good stats teachers, but they are sadly few and far between, and there are a lot of poor stats teachers who get in there in the mean time and deeply confuse me. I have a lot of good friends who try to teach me and I end up glazing over. What I mean to say is that the following is not personal – and it’s as much a criticism of myself as those who have tried to teach me . . .

Loads of statistically savvy people are willing to teach, they just don’t seem to get it through to me. So seeing as I’m supposed to be quite good at this education malarky, here’s my guide to teaching me statistics.

 

Make Sure We’re Speaking a Common Language

Yes, we really have to start with the basics here. Statistical language is incomprehensible to me. And that’s because we’re all taught differently.

As an example, I refer to response variables as ‘y’ and explanatory variables as ‘x’. A good friend of mine refers to explanatory variables as ‘y’ and response variables as ‘a’ or ‘b’. This causes huge confusion whenever we ask one another stats questions off the cuff.

And the common language refers to more than just making sure I understand what your big formulas are saying. This is what the homepage of R looks like. R is a sophisticated and free statistical tool that we should all be using. I’ve seen more intuitive GeoCities layouts. This is written by and for coders and I have to explain how to extract a zip file to some of my colleagues.

Why are you writing your R manual or your page about your fancy new statistical technique? Are you trying to share it with others who think like you? Fine, carry on. Are you trying to improve the statistical techniques used by frustrated, busy scientists who haven’t had more than a few week stats CPD a year?

Use your words.

Now the R Book is a good start for people wanting to learn R but I still wish it was written by Andy Field, who’s Discovering Statistics book is still my favourite bible, even though I don’t use SPSS anymore. If you’ve read both, you’ll see the difference in style is extreme, and I think it’s because, as a social scientist, Field has a better grasp of how people think. (Although speaking of GeoCities sites . . . I still love the book!)

Edited to Add: I lie! Andy Field has written an R textbook, which I have just bought! Thanks to Comparatively Psyched for the heads up! 

 

Teach Me Something I Can Use

This may seem counterintuitive to what I said further up, but if you’re trying to teach me, say, an alternative method to a stepwise regression, don’t just give me a dataset and tell me the code to run.

Tell me how to arrange my dataset in the way its needed. Ask me questions about my data – get me thinking about the complexities of the experiment I designed. And then tell me the code to run. Don’t forget to walk me through the output. For example, the documentation for the lars package in R explains how I can run a least angle regression on a sample dataset. Great. I can copy and paste that code ad libitum. Can I get it to work on my data? Even though to the best of my knowledge I’ve arranged it in the same way? Nope.

Get me to work through the whole process and you show me where your new method fits into my life.

 

What’s the Application?

I recently sat through a stats seminar where someone was showing off a new method. In the same presentation they briefly glossed over ternary plots as a way of showing off new data.

Applied scientists work in a world that judges us on the number of papers we produce and the impacts our papers have. That is literally how we get our baseline funding.

I don’t disagree that there are lots of problems with publishing but you’re asking me to relearn how I think about statistics, and then to communicate all this in a real-world paper with real-world data (that doesn’t always play nicely). If you’re asking somebody to use an amazing new technique, you’re asking them to get that past reviewers (who more often than not will not know your new stats).

If you have a great technique but it won’t actually give me a conclusion that I can use to improve animal welfare, then it’s not going to help me. And related to this . . .

 

What does it Mean?

The truth of the matter is that the statistical tests we commonly use are ‘plug and play’. We get into the habit of checking the things we want to look at noting the laundry list of caveats in a footnote.

Walk me through an example of what my results mean. If you’ve got me using my own data, tell me if this result confirms or denies my hypothesis, show me why, give me some indication of the next step.

I’m amazed at how many people don’t do this when trying to explain stats to me. You’re interested in the method, I get that. I’m fascinated by recording aggression in groups, but there’s a time and a place to discuss this, or just to tell you what aggression means.

 

Don’t Assume I’m Stupid

I see this all the time when statisticians are trying to teach something to scientists. They spend a very long time on the basics because our fundamentals are so scattered. This is not the most helpful approach. The other method I often see, when I say I don’t understand or even hesitate, the statistician repeats what they’ve said, more slowly and slightly louder.

We’re not stupid. Try teaching us a complex problem in an environment we’re familiar with (i.e. with our own data) and you’ll be surprised how many fundamental skills we’ll pick up because of it. To use a simple analogy, if you wanted to teach me how to maintain a car, wouldn’t you be be better off showing me how to take an engine apart rather than build one from scratch?

Don’t spend half our time explaining the problem to me – I get that there is a problem with the statistics I already use, it’s why I’ve sought you out. Is a finer understanding of the theory really going to help me use this test in future?

 

Finally – Why Are You Teaching Me?

This blog post sounds very whiny. Trust me, I know.

I know I should have learned all this earlier in my career. I know I should use R every day until I’m fluent. I know I shouldn’t using all these out of date stats. But the sad truth is that I haven’t, I don’t and I can’t.

I want to change, and I need the great community of statisticians to help me. So if you’re a statistician who wants to help me and people like me, this is how I’d suggest doing it.

Good luck!

Fluffy Friday – MOOC Countdown

In preparation for our MOOC, we’ve become a little obsessive. Every time I check the student count the numbers go up – we’re currently sitting at a staggering 19,129 students and roughly 6.7% of you have taken part in our little data gathering exercise we’ve sent out on the emails – so a big thank you for that.

At the moment you come from 153 different countries, and you span the age ranges of 13-70+.

We are so excited to meet all of you, and I have a little clip from the Jeanne Marchig YouTube channel of our third VLog.

Elephants Who Marry Mice

Don’t you just hate when you’re forced to face up to the fact you’re not as virtuous as you think you are?

One of the courses I’m currently writing for the International Fund for Animal Welfare came back to me with some corrections. My reviewer had changed the following sentence, the change in capitals.

“Dogs WHO showed pessimistic behaviours were more depressed.”

And try as I might, my gaze kept tripping over that word. Dogs Who, Dogs Who, Dogs Who.

Let us momentarily leap backwards in time to our English classes. My education contained very little formal grammar training, which may be obvious to the casual reader, but even I know that personal pronouns (e.g. who, he, she, they) are reserved for people. Animal are referred to as objects (e.g. which, it, that).

“The dog which barked” is preferable to “The dog who barked”.

“It is lying in the cat basket” may be preferable to “she is lying in the cat basket”.

This can lead to the English language treating animals very strangely. For example, say you visit a new acquaintance. You know this acquaintance has two cats, Gin and Tonic (this friend might be a bit odd), but you see one cat on the windowsill. You want to know, is that cat Gin or is that cat Tonic? You may ask “What cat is that?” or “Which cat is that?” seeing as you know it is one of two. It would be wrong to say “Who is that?”

Is it problematic to refer to animals as objects? Well first we have to ask if grammar affects the way we think. (And before we go any further I want to tell you that journals on grammar and semantics are almost as impenetrable as journals on molecular genetics)

Boroditsky (2009) investigated the differences in how speakers of English and Mandarin thought about time. In English we speak of time as a horizontal construct (you look ahead to the good times and back on the bad times) whereas in Mandarin time is spoken of in a vertical manner (the paper gives the translated example “what is the year before the year of the tiger?”).

The experiment itself is a bit odd to get your head around, but first they primed English and Mandarin speakers with either vertical or horizontal concepts (i.e. the black worm is ahead of the white worm, the black ball is below the white ball) and then given ‘target’ statements about time ‘March is earlier than April’, ‘March is before April’.

English speakers answered these questions faster after hearing a horizontal prime (similar to how they think of time) and Mandarin speakers answered these questions faster after they had heard a vertical prime (similar to how they think of time). Boroditsky concludes that the way we speak frames the way we perceive the world.

But does this happen in animal welfare? Well I’m not the only one who wondered about this. Gilquin & Jacobs (2006) wrote a paper which is whimsically titled ‘Elephants Who Marry Mice’. They reviewed style standards in various publication manuals. For example, the Guardian’s, which you can find here, says:

animals

pronoun “it” unless gender established

 

The Guardian also says:

any more

Please do not say “anymore” any more

 

So I don’t dream of writing a Comment Is Free column anymore.

Unsurprisingly, Gilquin and Jacobs found that it was the familiar animals (horses, dogs, cats, etc.) which scored a ‘who’ more often than the non familiar animals. Furthermore, publications aimed at animal-related interest groups were more likely to use ‘who’, e.g. Dogs Today.

They noted that in general texts or interviews, the personal pronoun was used when the author wanted to garner sympathy for the animal in question. It is “the poor cat who was stuck in a tree” rather than “the cat which was stuck in the tree”.

More interestingly, given some of my other posts on anthropomorphism, 60% of the sentences they found which used the personal pronoun for the animals attributed human-like characteristics to the animals.

Gilquin and Jacobs conclude that ‘who’ is used in English to refer to animals, although inconsistently. They suggest a wider adoption of this grammatical structure might engender more empathy for animals from humans, something which I think reflects what Ganea et al found in their work.

Should animal welfare scientists be calling for the personal pronoun usage?

I really can’t decide. I’m not convinced that it will completely change the way we think about animals. But it’s a nudge you might want to be aware of if you’re talking animal welfare science.

 

And for what it’s worth, I changed the text on the course.

The Anthropomorphism High Horse

I rarely read a piece of scientific journalism and think “what absolute tosh”, in part because I tend not to use the word ‘tosh’ and in part because I know that science journalism involves digesting and reconfirming a complex idea. It’s not easy.

But this article had me gnashing my teeth. It’s a summary of a paper by Ganea et al 2014 [in press pdf download – only link I can find]. The essence of the paper is this: children which grow up in urban environments (in this case pre-school age children from Boston and Toronto) are not exposed to animals. When they’re given anthropomorphic stories about unfamiliar animals (cavys, handfish and oxpeckers) they will agree with statements that attribute complex emotions to those animals, but not statements which attribute human physical capabilities, e.g. talking, to the animals. The conclusion is that anthropomorphic animal stories inhibit a child’s ability to learn animal facts.

The science I think is interesting – it is the conclusion and the bandying about of the word ‘anthropomorphism’ that get my goat. Let rant at you.

The article’s author says:

Setting aside the shades of grey as to whether non-human animals have analogues for things like friends, the findings suggest that for young kids, “exposure to anthropomorphized language may encourage them to attribute more human-like characteristics to other animals than exposure to factual language.”

 

 

This anthropomorphism spectre infuriates me at times. Let me put it this way, one of the questions asked of the children was “do oxpeckers have friends?” I’m asked relatively frequently if cows have friends, and if I want to answer that question accurately, I have to dance around terminology and use baffling scientific language to answer it in a way that means ‘yes but I can’t really say that because I’m a scientist’.

Cows have preferential associations within their herd. Being with these other individuals makes them more capable of physiologically coping with stressful events (Boissy & Le Neindre, 1997) such as being reintroduced to the milking herd (Neisen et al, 2009), being milked (Hasegawa et al, 1997), or feed competition (Patison et al, 2010a). They will preferentially engage in social interactions with these preferred associations, and these associations go on for longer than with other animals (Faerevik et al 2005, Patison et al, 2010b).

How do you explain this to a 2-5 year old child from Boston without using the word ‘friend’ or any synonym of it? Is it any wonder a child might reasonably assume that animals can have friends? Is it wrong to say that an animal can have a friend?

My irritation here lies with the writer of the article saying children believed ‘falsehoods’ about animals, based on anthropomorphism. We get one link, to a website I can’t access being based in the UK, to research which might suggest animals are similar to us in some ways. Then we move on to a paper I’ve referenced before talking about how dogs’ guilty looks are based on our behaviour (Hecht et al, 2012). The underlying assumption is still that animals are so different from us that children are wrong to believe that animals have the capacity for friendship and caring.

Now I’m fascinated by dogs for precisely this reason. They are so excellent at communicating with us, and reading us, that they are almost in-animal as much as they are in-human. They’re a possible model for human-child behaviour they’re so adept at this. I wouldn’t necessarily use dogs as an example for how the rest of the animal kingdom thinks if I was very worried about making cross species comparisons.

Anthropomorphism is either the attribution of human characteristics to animals. In which case it cannot be used pejoratively. For example, to say “This cow has eyes” would be anthropomorphic.

Or anthropomorphism is the inappropriate attribution of human characteristics to animals, in which case you must carefully consider why the characteristic is inappropriate when given to animals. It is not anthropomorphic in this case to say “This cow feels fear”, because fear, as we understand it, is an evolutionary mechanism to increase your chances of survival, it has physiological and behavioural components and the cow meets all of these. Ergo, this cow feels fear, and that is not an inappropriate characteristic.

Much as I lament the fact urban children have very little contact with the natural world, and I think this is a major issue for animal welfare, food sustainability, and the mental health of the children, I don’t fully agree with the paper’s conclusions, or the writing up in the Scientific American blog.

Firstly, the study found that all children learned new facts regardless of whether they read the anthropomorphic story or the non-anthropomorphic story. The results appear to indicate to me there was less fact-retention in the anthropromorphic story (and while I’m not a psychologist, I have worked with children and I do now work in education, I wonder if the anthropomorphic story, being similar to entertainment, indicated ‘you do not need to pay attention here’ to the kids. This does not appear to be discussed in the paper.).

Secondly, the study found that the children who had anthropoorphic stories told to them were more likely to describe animals in anthropomorphic terms immediately afterwards. Now again I’m no psychologist, but after I went to see Captain America I was partially convinced I was a superhero. It faded after the walk home. I’d like to know more about the extent of this effect over time before I declared anthropomorphic stories as damaging to children’s learning.

Thirdly, the Scientific American article presents some ‘realistic’ and ‘anthropomorphised’ images of the animals side by side. This is not what happened in the paper. In the first experiment the children were shown ‘realistic images and factual language books’ or ‘realistic images and anthropomoprhic language books’. The second study used ‘anthropomorphic images and factual language’ and ‘anthropomorphic images and anthropomorphic language’. The upshot of this is that the realistic image condition was not directly compared to the anthropormphic image condition, regardless of how it seems when you read the Scientific American article.

The paper says at one point:

This reveals that, like adults, young children seem to have a less clear conception of differences between humans and other animals in regard to mental characteristics, as opposed to behaviors. However, exposure to anthropomorphized language may encourage them to attribute more human-like characteristics to other animals than exposure to factual language.

 

 

Well there’s little wonder about that because even we scientists don’t have a particularly clear conception of the mental differences between humans and other animals. The paper itself is interesting and well worth a read, but it falls into the trap of thinking about anthropomorphism as a wholly negative thing. If I was a reviewer I’d suggest Serpell (2002) as an excellent starting point for a more balanced view of the phenomenon.

And I’d also suggest they watch this video before assuming that kids are daft for thinking animals feel emotions.

 

Knowledge Is Free . . .

. . . But Teaching is Priceless

Have you heard of a MOOC? It’s the latest buzzword in the further education sector and stands for Massive Open Online Course.

As part of my work I’m helping out with a few bits and pieces on one the University of Edinburgh’s MOOCs, Animal Behaviour and Welfare. (Well, you didn’t think I’d be helping on the astrophysics one, did you?)

I’m aware that I’m failing at getting a fortnightly blog out there and considering I spent the last two days sorting students, lecturing, writing KT presentations and listening to discussions about MOOCs, I thought it would be an excellent opportunity to talk about some of the ways we can exchange knowledge with a wide audience.

The University of Edinburgh have chosen Coursera as their platform for delivering MOOCs. Each MOOC is 4-7 weeks long, is aimed at a general audience, but delivered remotely by university staff. You can take a MOOC because you’re interested in the subject, because you want to know if a subject is something you might like to study in the future, because you want to demonstrate interest in Continued Professional Development to your employer, and in some cases even to get a few university credits.

The numbers of users on these courses is staggering, with thousands of people actually finishing the course. But, like many new ideas, there is some resistance to them within the academic community.

One of the issues is: who are we really aiming these at? The user base is so huge and so diverse that trying to pitch a course can be difficult. There’s some hope that we can use these as taster sessions for our Masters courses, but if they’re interesting for someone who has the pre-requisite knowledge for a Masters course, will they be accessible enough for the layperson?

The Equine Nutrition MOOC which ran last year did end up recruiting some future Masters students, but it was also hugely successful with the horse owning populace. It is possible to strike that balance, at least for an audience with enough interest and motivation to complete the course. It’s something to be aware of – the old saying is more true than ever: Know your audience.

Another issue is the level of work involved. While they’re intended to be short courses, videos, quizzes, resources amalgamations, I’ve heard the tutors say its hard to walk away from people who want extra support. As someone who schedules ten minutes ‘I’m here to be talked to’ time at the end of every lecture, I get that. Students like to talk. They like support. And I think they deserve support. Anyone who wants to learn deserves a little attention, but when so many people want to learn, how do you split your attention? I’d be interested in knowing how internet literate these users tend to be. After establishing a user base, would it become possible to initiate users who had completed the course as forum mods? As we say on the IRC channels, half ops to our ops?

I think this might be part of the problem. Academia may have been where the internet was invented, but not all of us are wonderfully computer literate ourselves. In my experience, internet communities can be great places, but they work best when they have a strong, recognised leader (Shout out to any of my Bungie.Org friends who followed the advertising links! We all know who our fearless leader is). I could imagine MOOCs becoming great places for people to congregate, to find out information from good, recognisable sources, and to help each other learn.

But I can also see MOOCs falling victim to academia’s other big problem: where’s the money? The courses cost money to make, and the revenue path is not clear. I’ve been thinking about this over the last few days and I’ve come down on the idea that we have to put MOOCs under the umbrella of ‘knowledge transfer’. It’s a way of communicating structured information to a large audience, cheaply. My personal opinion (and do remember that all opinions expressed on this blog are mine and do not necessarily reflect those of my employers and colleagues) is that you can’t look at a MOOC as a money making exercise. But does that mean that the students can’t expect to be treated like customers?

What I can say is that the next couple of years are going to be fascinating for further education.