Students
Statistics - some myths debunked
STATS blues? See red at the mere thought of SPSS? Green with envy at
the more statistically minded in your department? When it comes to
stats, our thinking is coloured by associations with maths and a
generally scary reputation. I can see a self-fulfilling prophecy in the
making, so let’s debunk a few myths.
You have to be good at maths to be good at stats As Professor Christine Dancey, co-author of Statistics Without Maths for Psychology, told me, ‘we have
to remember as psychologists that statistics are tools that we use, we
don’t need to learn statistics for its own sake’. Her book hardly has a
formula in its 636 pages. What is more important than maths is the
ability to relate statistical techniques to real-life examples.
Stats are OK, but SPSS overcomplicates it all SPSS For Windows is there to simplify our life by carrying out all the calculations for us.
The ‘Help’ pages of the package are very informative, and yet few
people bother to use them! Stats books have helpful annotated pictures
of SPSS showing how to input data and how to read the output, and there
are also books dedicated to the use of SPSS, notably SPSS for
Psychologists by Nicola Brace et al. and Paul Kinnear and Colin Gray’s
SPSS 12 Made Simple. They take you through every single command, button
and function you can think of, and they explain what those scary tables
in the output really mean.
Speaking of scary tables, some students seem to think that the results
section of a lab report is an exercise in ‘copy object’ and ‘paste’. As
Paul Kinnear notes, ‘ANOVA tables can be particularly obscure without
appropriate editing’, and the way you edit them shows whether you can
separate and retain only the important elements. Indeed, this is a good
time to check your understanding of the procedure you are using. Of
course, the temptation is there to keep, say, the Huynh-Feldt line,
just in case it was what the lecturer talked about that day I bunked
off/was surreptitiously listening to my MP3 player while hiding behind
my big mate at the back of the class…
The fancier the technique, the better
This is the ‘divination’ approach to data collection and analysis and
is particularly applied to final-year projects, when a student
experiences the giddy freedom to develop their own design. Like a
clairvoyant waiting for a picture to emerge from coffee grounds, the
student expects something meaningful to arise from the trail of SPSS
output. It’s got to happen! After all the variables I put in, and all
the fancy techniques I used.
Well, contrary to popular belief, less can be more. Why complicate
one’s life (and expose one’s incompetence) by choosing a complex
inferential test when a t test would do? Statistics are tools and the
trick is to know why and how to use them. What are we hoping to find?
What do we need to get there? There is no substitute for a clear design
in your mind, bringing home again the importance of conceptual
understanding (and of the saying, ‘garbage in, garbage out’).
Phew! So glad to see the back of the t test – Luckily we’re not going to use it next year
Perhaps the most important principle of statistics is that you build
brick by brick, in manageable stages (so that it is not too daunting).
If the foundations have disappeared or were very shaky in the first
place, no wonder that the edifice you are trying to build will not
stand.
The importance of making links is reiterated by Andy Field, author of
Discovering Statistics Using SPSS for Windows: ‘…continuity is really
important. I tend to emphasise the similarities between different
statistical procedures and as we move onto new topics I try to
constantly refer back to previous lectures and so on. So, for example,
my students (much to their horror, I’m sure) get reminded of what a
model sum of squares is in pretty much every lecture for 13 weeks!’
Who cares about stats? I’m going into ‘qualitative’ research anyway.
In research practice quantitative and qualitative research methods
complement and illuminate each other, and in many ways this dichotomy
is artificial. If you would still like to tell statisticians what to do
with their normal curve, it is a good idea to know what it is meant by
‘normal curve’ first! Sure, it is not merely a matter of methodology;
the issues are further upstream at epistemological level. But – and I
speak as a social constructionist –
the best possible critique can be developed when there is an
understanding of the assumptions and procedures used by the
‘quantitative’ camp.
Having debunked some common myths, let’s hope that ‘stats anxiety’ as
felt at Time 1 (before reading this short article) has substantially
decreased (ideally close to 0) at Time 2! If you need more, see my
interviews with stats books authors in PsychTalk this year.
- Toni Brennan is in the Department of Psychology, University of Surrey. E-mail: [email protected].
ONLINE FORUM
Have you visited The Psychologist’s online forum yet? There are
three different sections, and students might be particularly interested
in using them to:
l discuss and debate the latest developments in psychology, and articles you have read in The Psychologist.
l seek information, or voluntary work, or sponsorship
if you are planning a fundraising activity for a psychology-related
charity (for example in March I am trekking across the Sahara for
Mencap).
l ask a question, whether it is serious or off-beat.
See www.thepsychologist.org.uk and click on ‘forum’ for more.
Nicola Hills (Associate Editor for the Student page: E-mail [email protected])
(Please note that some pictures may have been removed for copyright reasons)
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