The seven deadly sins of statistical misinterpretation, and how to avoid them

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Where are the error bars? (Shutterstock)

Winnifred Louis, The University of Queensland and Cassandra Chapman, The University of Queensland

Statistics is a useful tool for understanding the patterns in the world around us. But our intuition often lets us down when it comes to interpreting those patterns. In this series we look at some of the common mistakes we make and how to avoid them when thinking about statistics, probability and risk. The Conversation


1. Assuming small differences are meaningful

Many of the daily fluctuations in the stock market represent chance rather than anything meaningful. Differences in polls when one party is ahead by a point or two are often just statistical noise.

You can avoid drawing faulty conclusions about the causes of such fluctuations by demanding to see the “margin of error” relating to the numbers.

If the difference is smaller than the margin of error, there is likely no meaningful difference, and the variation is probably just down to random fluctuations.

Error bars illustrate the degree of uncertainty in a score. When such margins overlap, the difference is likely to be due to statistical noise.


2. Equating statistical significance with real-world significance

We often hear generalisations about how two groups differ in some way, such as that women are more nurturing while men are physically stronger.

These differences often draw on stereotypes and folk wisdom but often ignore the similarities in people between the two groups, and the variation in people within the groups.

If you pick two men at random, there is likely to be quite a lot of difference in their physical strength. And if you pick one man and one woman, they may end up being very similar in terms of nurturing, or the man may be more nurturing than the woman.

You can avoid this error by asking for the “effect size” of the differences between groups. This is a measure of how much the average of one group differs from the average of another.

If the effect size is small, then the two groups are very similar. Even if the effect size is large, the two groups will still likely have a great deal of variation within them, so not all members of one group will be different from all members of another group.


3. Neglecting to look at extremes

The flipside of effect size is relevant when the thing that you’re focusing on follows a “normal distribution” (sometimes called a “bell curve”). This is where most people are near the average score and only a tiny group is well above or well below average.

When that happens, a small change in performance for the group produces a difference that means nothing for the average person (see point 2) but that changes the character of the extremes more radically.

Avoid this error by reflecting on whether you’re dealing with extremes or not. When you’re dealing with average people, small group differences often don’t matter. When you care a lot about the extremes, small group differences can matter heaps.


4. Trusting coincidence

Did you know there’s a correlation between the number of people who drowned each year in the United States by falling into a swimming pool and number of films Nicholas Cage appeared in?

Is there a causal link? (tylervigen.com)

If you look hard enough you can find interesting patterns and correlations that are merely due to coincidence.

Just because two things happen to change at the same time, or in similar patterns, does not mean they are related.

Avoid this error by asking how reliable the observed association is. Is it a one-off, or has it happened multiple times? Can future associations be predicted? If you have seen it only once, then it is likely to be due to random chance.


5. Getting causation backwards

When two things are correlated – say, unemployment and mental health issues – it might be tempting to see an “obvious” causal path – say that mental health problems lead to unemployment.

But sometimes the causal path goes in the other direction, such as unemployment causing mental health issues.

You can avoid this error by remembering to think about reverse causality when you see an association. Could the influence go in the other direction? Or could it go both ways, creating a feedback loop?


6. Forgetting to consider outside causes

People often fail to evaluate possible “third factors”, or outside causes, that may create an association between two things because both are actually outcomes of the third factor.

For example, there might be an association between eating at restaurants and better cardiovascular health. That might lead you to believe there is a causal connection between the two.

However, it might turn out that those who can afford to eat at restaurants regularly are in a high socioeconomic bracket, and can also afford better health care, and it’s the health care that affords better cardiovascular health.

You can avoid this error by remembering to think about third factors when you see a correlation. If you’re following up on one thing as a possible cause, ask yourself what, in turn, causes that thing? Could that third factor cause both observed outcomes?


7. Deceptive graphs

A lot of mischief occurs in the scaling and labelling of the vertical axis on graphs. The labels should show the full meaningful range of whatever you’re looking at.

But sometimes the graph maker chooses a narrower range to make a small difference or association look more impactful. On a scale from 0 to 100, two columns might look the same height. But if you graph the same data only showing from 52.5 to 56.5, they might look drastically different.

You can avoid this error by taking care to note graph’s labels along the axes. Be especially sceptical of unlabelled graphs.


Winnifred Louis, Associate Professor, Social Psychology, The University of Queensland and Cassandra Chapman, PhD Candidate in Social Psychology, The University of Queensland

This article was originally published on The Conversation. Read the original article.

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ANU Biological Anthropology Research (BAR) 2017 Seminar Schedule

bar

Australian National University

BIOLOGICAL ANTHROPOLOGY RESEARCH
BAR SEMINARS 2017

Thursdays 4pm, Jean Martin Room, Level 3 Beryl Rawson Building 13

February 23rd
Dr Rita Hardiman
University of Melbourne
The Melbourne Femur Research Collection: From forensic anthropology to multi-disciplinary research collection of international significance

March 2nd
Megan O’Donnell
Australian National University
The Phoenix Cohort: The effects of bushfire stress in utero

March 16th
Dr Tanya Smith
Griffith University
How teeth shed light on our evolutionary past

March 23rd
Prof Robert Brooks
University of New South Wales
The value of rarity in sexual behaviour

April 6th
Dr Vicky Melfi
Taronga Conservation Society Australia
Behavioural Biology title TBC

May 4th
Clare McFadden
Australian National University
Parturition Scars

May 18th
Dr Emiliano Bruner
Centro Nacional de Investigación sobre la Evolución Humana, Spain; and University of Colorado, US
Fossils, skulls, and brains: bridging paleoneurology and medicine

July 27th
Dr Siân Halcrow
University of Otago, NZ
The once forgotten child in bioarchaeology: developments in the field

August 17th
Dr David Coall
Edith Cowan University
The crucial role of the early psychosocial environment in human reproductive developmental plasticity: an evolutionary perspective

August 31st
Dr Alison Behie
Australian National University
Human and primate adaptations to changing environments

September 21st
Dr Cyril Grueter
University of Western Australia
Sexual selection and primate multilevel societies

October 5th
Dr Caroline Bennett
Victoria University of Wellington, NZ
What do we do when we dig up mass graves?

October 19th
Dr Varsha Pilbrow
University of Melbourne
The Great Ape Dental Scoring System and a single case-study of its application to human evolutionary research

Twitter: @ANU_BioAnth | Event enquires: Justyna.Miszkiewicz@anu.edu.au

PDF BAR Schedule 2017 – for posting

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ANU Biological Anthropology Seeks Primatologist for 3-Year Fixed Appointment

anu_logo_stacked_rgbLecturer in Biological Anthropology

Job no: 515459
Work type: Fixed Term
Location: Canberra / ACT
Categories: Academic

Classification: Academic Level B
Salary package: Level B: $91,541 – $104,254 per annum plus 17% Superannuation
Term: Full time, 3 years fixed term

Position overview

The School of Archaeology and Anthropology in the ANU College of Arts and Social Sciences is seeking to make a 3 year fixed term appointment in biological anthropologist specialising in primatology to contribute to its research and teaching program, commencing in July 2017. We seek to appoint a lecturer with an active commitment to research, who is able to translate that research interest into lively and engaging courses taught at the undergraduate level and above, and to supervise postgraduate research students. That person will be able to demonstrate energy and expertise in teaching, research and publication, at an early-career level.

Complete information available here:
http://jobs.anu.edu.au/cw/en/job/515459/lecturer-in-biological-anthropology

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Can’t Wait to See You in My Courses in Semester 1 of 2017!

The 2016 academic year is coming to a close here at The Australian National University. Five semesters under my belt, and I feel like I’m finding my groove. We’re starting to advertise our classes for Semester 1 of the 2017 academic year, starting in February, so I thought I’d share the posters for the two classes I’ll be teaching.

I’m very excited to be teaching two courses so closely related to my research interests and expertise in human behavioural ecology in the same semester. You bet I’ll be talking a lot about my own research in these courses:

  • ‘Evolution and Human Behaviour’ (BIAN 3124/6124)
  • ‘Mating and Parenting’ (BIAN 2133/6133)

Do either of these classes sound interesting to you? If so, I’d love to have you. As always, I’ll be keeping my eye out for star performers ready to join the ranks of my honours, masters, and PhD students!

BIAN 3124 6124 poster.PNG

BIAN 2133 6133 poster.PNG

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ANU Students Critically Evaluate Popular Books on Human Evolution

20161011_122152.jpgWhy do men and women look for different things in a significant other? What can the behaviour of other animals tell us about human behaviour? Are popular books on the topic oversimplified? Or can we learn something of value from them?

The students in my course at The Australian National University explored these issues and others, while sharing their critical evaluations of popular literature on human evolution this week in a Poster Faire.

They produced the posters as a requirement for the course ‘Sexual Selection and Human Evolution’ (BIAN 2132/6132).

And they had great fun doing it! The course’s 56 enroled students were split into 3 groups. Each group presented for 1 hour, and then each student came to serve as the audience for one of the other hours. And, the students enjoyed it:

“The poster faire really served as an interactive platform where students were able to give their perspectives on some very interesting topics and was a fun way to dive deeper into the course material. I definitely gained new insights and really have been persuaded to read some of the books that were presented. ” – Inez Derkx

Click here to see the Poster Faire Gallery — high-resolution images of posters, and some additional photos of the Poster Faire and the participants.

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What exactly are Anthropology MAs doing with their anthropology?

Great blog post about what anthropology MAs do after graduation by Chrislyn Laurore.

Welcome to the AAA Blog

This post was authored by AAA summer intern Chrislyn Laurore, a recent graduate of the anthropology program at Mount Holyoke College.

It took all of thirty minutes into my Intro to Cultural Anthropology class during the very first semester of my undergrad degree to decide that anthropology was it for me. A first-generation American eager to learn more about the world while validating my own experiences, entering the realm of anthropology began to answer many of the burning questions I had long thought about but had been unable to articulate. Nothing would derail my enthusiasm. Not even the now-familiar, “Anthropology? What on Earth are you going to do with that?” parroted by well-meaning strangers and relatives alike.

Having taken on a part time job in my college’s admissions office, I became a pro at assuring prospective students, parents – and myself – that you can do anything with your liberal arts degree. But…

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How to Read for Grad School

Looks like great advice!

Miriam E. Sweeney

Books

In graduate school the work load increases and students will find that they are expected to master two to three times the material that they were used to as an undergraduate.  This can be intimidating to the point of overwhelming a student into paralysis.  Following these tips should help you master your readings instead of allowing the readings to master you!

1.     Read Strategically, Not Linearly. Reading for graduate school is different than reading a book for pleasure.  When we read for pleasure we often start at the beginning of the book, reading carefully in a linear fashion.  If you do this with your academic material, it will take twice as long and it is likely you won’t retain the right kind of information from the reading.  Instead of reading linearly, read strategically.  As an academic reader your job is to mine the text you are reading for information. …

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