When
I
wrote the first edition of this book
I
was writing as an A-level teacher knowing
that we
all
needed a comprehensive book of methods and statistics which didn't then
exist at the appropriate level.
I
was pleasantly surprised, therefore, to find an
increasing number of Higher Education institutions using the book as an intro-
ductory text.
In
response to the interests of higher education students,
I
have
included chapters on significance tests for three or more conditions, both non-
parametric and using ANOVA. The latter takes the student into the world of the
interactions which are possible
with
the use of more than one independent variable.
The point about the 'maths' involved in psychological statistics still holds true,
however. The calculations involve no more than those on the most basic calculator
-
addition, subtraction, multiplication and division, squares, square roots and deci-
mals. The chapter on other useful complex tests is meant only as a signpost to readers
venturing further into more complex designs and statistical investigation.
Although this introduction of more complex test procedures tends to weight the
book further towards statistics, a central theme remains the importance of the whole
spectrum of possible research methods in psychology. Hence,
I
have included a brief
introduction to the currently influential,
if
controversial, qualitative approaches of
discourse analysis and reflexivity, along with several other minor additions to the
variety of methods. The reader will find a general updating of research used to
exemplify methods.
In
the interest of studeit learning through engagement with the text,
I
have
included a glossary at the end of each chapter which doubles as a self-test exercise,
though A-level tutors, and those at similar levels,
will
need to point out that students
are not expected to be familiar with every single key term. The glossary definition for
each term is easily found by consulting the main index and turning to the page
referred to in heavy type. To stem the tide of requests for sample student reports,
which the first edition encouraged,
I
have written a bogus report, set at an 'average'
level
(I
believe), and included possible marker's comments, both serious and hair-
splitting.
Finally,
I
anticipate, as with the fist edition, many enquiries and arguments
critical of some of my points, and these
I
welcome. Such enquiries have caused me to
alter, or somewhat complicate, several points made in the first edition. For instance,
we lose Yates' correction, find limitations on the classic Spearman's rho formula,
learn that correlation with dichotomous (and therefore nominal) variables
is
possible,
and so on. These points do not affect anything the student needs to know for their
A-level exam but may affect procedures used in practical reports. Nevertheless,
I
have withstood the temptation to enter into many other subtle debates or niceties
simply because the main aim of the book is still, of course, to clarify and not to
confuse through density.
I
do hope that this
aim
has been aided by the inclusion of yet
more teaching 'tricks' developed since the last edition, and, at last, a few of my
favourite illustrations.
If
only some of these could move!
Hugh Coolican
PARTONE
Introduction
This introduction sets the scene for research in psychology. The key ideas are
that:
Psychological researchen generally follow a scientific approach.
This involves the logic oftesting hypotheses produced from falsifiable theories.
Hypotheses need to be precisely stated before testing.
Scientific research is a continuous and social activity, involving promotion and
checking of ideas amongst colleagues.
Researchers use probability statistics to decide whether effects are 'significant'
or not.
Research has to be carefully planned with attention to design, variables,
samples and subsequent data analysis. If
all
these areas are not fully planned,
results may be ambiguous or useless.
Some
researchen have strong objections to the use of traditional scientific
methods in the study of persons. They support qualitative and 'new paradigm'
methods which may
not
involve rigid pre-planned testing of hypotheses.
Student: I'd like to enrol for psychology please.
Lecturer: You do realise that it includes quite a bit of statistics, and you'll
have to do some experimental work and write up practical
reports?
Student: Oh.
.
.
When enrolling for a course
in
psychology, the prospective student is very often taken
aback by the discovery that the syllabus includes a fair-sized dollop of statistics and
that practical research, experiments and report-writing are all involved. My experi-
ence as a tutor has commonly been that many
'A'
level psychology students are either
'escaping' from school into fixther education or tentatively returning after years away
from academic study. Both sorts of student are frequently dismayed to find that
this
new and exciting subject is going to
thrust
them back into two of the areas they most
disliked
in
school. One is maths
-
but rest assured! Statistics,
in
fact, will involve you
in
little of he maths on a traditional syllabus and
will
be performed on real data most
of which you have gathered yourself. Calculators and computers do the 'number
crunching' these days. The other area is science.
It
is strange that of all the sciences
-
natural and social
-
the one which directly
concerns ourselves as individuals in society is the least likely to be found in schools,
where teachers are preparing young people for social life, amongst other thiigs! It is
also strange that a student can study all the 'hard' natural sciences
-
physics,
chemistry, biology
-
yet never be asked to consider what a science
is
until
they study
psychology or sociology.
These are generalisations of course. Some schools teach psychology. Others
nowadays teach the underlying principles of scientific research. Some of us actually
enjoyed science and maths at school.
If
you did, you'll find some parts of this book
fairly easy going. But can
I
state one of my most cherished beliefs right now, for the
sake of those who hate numbers and think this is all going to be a struggle, or, worse
still, boring? Many of the ideas and concepts introduced in this book will already be
in your head in an informal way, even 'hard' topics like probability. My job is
to
give names to some concepts you will easily think of for yourself. At other times it will
be to formalise and tighten up ideas that you have gathered through experience. For
instance, you already have a fairly good idea of how many cats out of ten ought to
choose 'Poshpaws' cat food in preference to another brand, in order for us to be
convinced that this is a real Merence and not a fluke. You can probably start
discussing quite competently what would count as a representative sample of people
for a particular survey.
Returning to the prospective student then, he or she usually has little clue about
what sort of research psychologists do. The notion of 'experiments' sometimes
produces anxiety. 'Will we be conditioned or brainwashed?'
If
we ignore images from the black-and-white
film
industry, and
think
carefully
about what psychological researchers might do, we might conjure up an image of the
street survey.
Think
again, and we might suggest that psychologists watch people's
behaviour.
I
agree with Gross (1992) who says that, at a party,
if
one admits to
teaching, or even studying, psychology, a common reaction is 'Oh, I'd better be
careful what
I
say from now on'. Another strong contender is
'I
suppose you'll be
analysing my behaviour' (said as the speaker takes one hesitant step backwards) in the
mistaken assumption that psychologists go around making deep, mysterious inter-
pretations of human actions as they occur. (If you meet someone who does do this,
ask them something about the evidence they use, after you've finished with this
book!) The notion of such analysis is loosely connected to Freud who, though
popularly portrayed as a psychiatric Sherlock Holmes, used very few of the sorts of
research outlined in this book
-
though he did use unstructured clinical interviews
and the case-study method (Chapter
8).
SO
WHAT IS THE NATURE OF PSYCHOLOGICAL
Although there are endless and furious debates about what a science is and what son
of science,
if
any, psychology should be, a majority of psychologists would agree that
research should be scientific, and at the very least that it should be objective,
controlled and checkable. There is no final agreement, however, about precisely how
scientific method should operate
within
the very broad range of psychological
research topics. There are many definitions of science but, for present purposes,
Allport's
(1
947) is useful. Science, he claims, has the aims of:
'.
. .
understanding, prediction and control above the levels achieved by
unaided common sense.'
What does Allport, or anyone, mean by 'common sense'? Aren't some things blindly
obvious? Isn't it indisputable that babies are born
with
different personalities, for
instance? Let's have a look at some other popular 'common-sense' claims.
I
have used these statements, including the controversial ones, because they are just
the sort of things people claim confidently, yet with no hard evidence. They are
'hunches' masquerading as fact. I call them 'armchair certainties (or theories)'
because this is where they are often claimed from.
Box I. I
'Common-sense' claims
1
Women obviously have a maternal
instinct
-
look how strongly they want to
stay with their child and protect
it
2
Michelle is so good
at
predicting people's
star sign -there must be something in
astrology
3
So many batsmen get out on
98
or
99
-
it
must be the psychological pressure
Have we checked how men would feel
after several months alone with a baby?
Does the
tern 'instinct'
odd
to our
understanding,
or
does
it
simply describe
what mothers do and, perhaps, feel? Do
all
mothers feel this way?
Have we checked that Michelle gets a lot
more signs correct than anyone would by
just guessing? Have we counted the times
when she's wrong?
Have we compared with the numbers of
batsmen who get out on other high totals?
4
Women are less logical, more suggestible
Women score the same as men
on
logical
-
and
make worse drivers than men
tests in general. They are equally
'suggestible', though boys are more likely to
agree with views they don't hold but which
are held by their peer group. Statistically,
women are more -likely to obey traffic rules
and have less expensive accidents. Why else
would 'one lady owner' be a selling point?
5
1
wouldn't obey someone who told me
About
62% of people who could have
to seriously hurt another person if
I
could
walked free from
an experiment, continued
possibly avoid
it
to obey an experimenter who asked them
to give electric shocks to a 'learner' who
had fallen silent
after screaming horribly
6
The trouble with having so many black
In 199 I, the total black population of the
immigrants
is
that the country is too
UK
(African Caribbean and Indian sub-
small' (Quote from
Call
Nick
Ross
phone-
continental Asian) was
a
little under
5%.
in, BBC Radio 4,3.1 1.92)
Almost every year since the second world
war, more people haye left than have
entered Britain to live. Anyway,
whose
country?
I
hope you see why we need evidence from research. One role for a scientific study is
to challenge 'common-sense' notions by checking the facts. Another is to produce
'counter-intuitive' results like those in item five. Let me say a little more about what
scientific research is by dispelling a few myths about it.
MYTH NO. I: 'SCIENTIFIC RESEARCH IS THE COLLECTION OF FACTS'
All
research is about the collection of data but this is not the sole aim. First of all, facts
are not data. Facts do not speak for themselves. When people say they do they are
omitting to mention essential background theory or assumptions they are making.
A
sudden crash brings us running to the kitchen. The accused is crouched
in front of us, eyes wide and fearful. Her hands are red and sticky.
A
knife
lies on the floor. So does a jam jar and its spilled contents. The accused
was about to lick her tiny fingers.
I
hope you made some false assumptions b'efore the jam was mentioned. But, as it is,
do the facts alone tell us that Jenny was stealing jam? Perhaps the cat knocked the jam
over and Jenny was trying to pick it up. We constantly assume a lot beyond the
present data in order to explain it (see Box 1.2). Facts are
DATA
interpreted through
THEORY.
Data are what we get through
EMP~CAL
observation, where 'empirical'
refers to information obtained through our senses. It is difficult to get raw data. We
almost always interpret it immediately. The time you took to
run
100 metres (or, at
least, the position of the watch hands) is raw data. My saying you're 'quickJ is
interpretation.
If
we lie on the beach looking at the night sky and see a 'star' moving
steadily we 'know' it's a satellite, but only because we have a lot of received
astronomical knowledge, from our culture, in our heads.
Box 1.2
Fearing or clearing the bomb?
'
In psychology we conbntly challenge the simplistic acceptance of fa&
'in
front of our
,
eyes'.
A
famous bomb disposal officer, talking to Sue Lawley on
Desert
lslond
Discs,
told of
i
the time he was trying urgently to clearthe public from the area of a live bomb.
A
I
newspaper published hk picture, advancing with outstretched arms, with the caption,
I
'terrified member of public flees bomb', whereas another paper correctly identified him as
the calm,
but
concerned expert he really was.
Data are interpreted through what psychologists often call a 'schema'
-
our learned
prejudices, stereotypes and general ideas about the world and even according to our
current purposes and motivations.
It
is difficult to see, as developed adults, how we
could ever avoid this process. However, rather than despair of ever getting at any
psychological truth, most researchers share common ground in following some basic
principles of contemporary science which date back to the revolutionary use of
EMPIRICAL
METHOD
to start questioning the workings of the world in a consistent
manner.
The empirical method
The original empirical method had two stages:
1
Gathering of data, directly, through our external senses, with no preconceptions
as to how it is ordered or what explains it.
2
IN~ucnoN of patterns and relationships within the data.
'Induction' means to move &om individual observations to statements of general
patterns (sometimes called 'laws').
fa
30-metre-tall Maman made empirical observations on Earth, it (Martians have
one
sex) might focus its attention on the various metal tubes which hurtle around,
some
in
the air, some on the ground, some under it, and stop every so often to take on
little bugs and to shed others.
The Martian might then conclude that the tubes were important life-forms and
that the little bugs taken on were food
.
.
.
and the ones discharged
. .
.
?
Now we have gone beyond the original empirical method. The Martian is
the0
y.
This is an attempt to explain
why
the patterns are produced, what
forces or processes underly them.
It is inevitable that human thinking will go beyond the patterns and combinations
discovered in data analysis to ask, 'But why?'. It is also naive to assume we could ever
gather data without some background theory in our heads, as
I
tried to demonstrate
above. Medawar (1963) has argued this point forcefully, as has Bruner who points
out that, when we perceive the world, we always and inevitably 'go beyond the
information given'.
Testing theories
-
the hypothetico-deductive method
This Martian's theory, that the bugs are food for the tubes, can be tested.
If
the tubes
get no bugs for a long time, they should die. This prediction is a
HYPOTHESIS.
A
hypothesis is a statement of exactly what should be the case $a certain theory is true.
Testing the hypothesis shows that the tubes can last indefinitely without bugs. Hence
the hypothesis is not supported and the theory requires alteration or dismissal. This
manner of thinking is common in our everyday lives. Here's another example:
Suppose you and a friend find that every Monday morning the wing mirror
of your car gets knocked out of position. You suspect the
dustcart which
empties the bin that day. Your fiend says, 'Well, OK. If you're so sure
let's check next Tuesday. They're coming a day later next week because
there's a Bank Holiday.'
The logic here is essential to critical
thinking in psychological research.
The
theory
investigated is that the dustcart knocks the mirror.
The
hypothesis
to be tested is that the mirror will be knocked next Tuesday.
Our
test
of the hypothesis is to check whether the mirror
is
knocked next Tuesday.
*
If
the mirror
is
knocked the theory is
supported.
If
the mirror is
not
knocked the theory appears wrong.
Notice, we say only 'supported' here, not 'proven true' or anything definite like that.
This is because there could be an alternative reason why it got knocked. Perhaps the
boy who follows the cart each week on his bike does the knocking. This is an example
of 'confounding' which we'll meet formally in the next chapter. If you and your friend
were seriously scientific you could rule this out (you could get up early). This
demonstrates the need for complete control over the testing situation where
possible.
We say 'supported' then, rather than 'proved', because D (the dustcart) might not
have caused
M
(mirror getting knocked)
-
our theory. Some
other
event may have
been the cause, for instance
B
(boy cycling with dustcart). Very often we
think
we
have evidence that
X
causes
Y
when, in fact, it may well be that Y causes
X.
You
might think that a blown fuse caused damage to your washing machine, which now
won't
run,
when actually the machine broke, overflowed and caused the fuse to blow.
In
psychological research, the theory that mothers talk more to young daughters
(than to young sons) because girls are naturally more talkative, and the opposite
theory, that girls are more talkative because their mothers talk more to them are both
supported by the evidence that mothers do talk more to their daughters. Evidence is
more useful when it supports one theory and
not
its rival.
Ben Elton (1989) is onto this when he says:
Lots of Aboriginals end up as piss-heads, causing people to say 'no wonder
they're so poor, half of them are piss-heads'. It would, of course, make
much more sense to say 'no wonder half of them are piss-heads, they're so
-
poor'.
Deductive logic
Theory-testing relies on the logical arguments we were using above. These are
examples of
DEDUCTION.
Stripped to their bare skeleton they are:
Applied to the0 y-testing
Applied to the dustcart and
mirror problem
1
If
X
is true then
Y
must
1
If theory
A
is true, then
1
If the dustcart knocks
be true hypothesis H
will
be the mirror then the mir-
coniirmed ror will get knocked
next Tuesday
2
Y isn't true
2
H is disconfinned
2
The mirror didn't get
knocked
3 Therefore
X
is not true 3 Theory A is wrong*
3 Therefore it isn't the
dustcart
or or
2
Yistrue
2
H is coniirmed
2
The mirror
did
get
knocked
3
X
could still be true
3 Theory
A
could be true
3
Perhaps it
is
the dust-
cart
*At this point, according to the 'official line', scientists should drop the theory with
the false prediction. In fact, many famous scientists, including Newton and Einstein,
and most not-so-famous-ones, have clung to theories
despite
contradictory results
because of a 'hunch' that the data were wrong. This hunch was sometime shown to
be correct. The beauty of a theory
can
outweigh pure logic in real science practice.
It is often not a lot of use getting more and more of the same sort of support for your
theory. If I claim that all swans are white because the sun bleaches their feathers, it
gets a bit tedious if I keep pointing to each new white one saying 'I told you so'.
AU
we
need is one sun-loving black swan to blow my theory wide apart.
If your hypothesis is disconiirmed, it is not always necessary to abandon the theory
which predicted it, in the way that my simple swan theory must go. Very often you
would have to adjust your theory to take account of new data. For instance, your
friend might have a smug look on her face. 'Did you know it was the Council's "be-
ever-so-nice-to-our-customers" promotion week and the collectors get bonuses
if
there are no complaints?' 'Pah!' you say 'That's no good as a test then!' Here, again,
we see the need to have complete control over the testing situation in order to keep
external events as constant as possible. 'Never mind,' your fiend soothes, 'we can
always write this up in our psychology essay on scientific method'.
Theories in science don't just get 'proven true' and they rarely rest on totally
evidence. There is often a balance in favour with several anomalies yet
to explain. Theories tend to 'survive' or not against others depending on the quality,
not just the quantity, of their supporting evidence. But for every
single
supportive
piece of evidence in social science there is very often an alternative explanation. It
might be claimed that similarity between parent and child in intelligence is evidence
for the view that intelligence is genetically transmitted. However, this evidence
supports
equally
the view that children
learn
their skills from their parents, and
similarity between adoptive parent and child is a
challenge
to the theory.
Fakz3a
bility
popper (1959) has argued that for any theory to count as a theory we must at least be
able to see how it
could
be falsified -we don't have to be able to falsify it; after all, it
might be true! As an example, consider the once popular notion that Paul McCartney
died some years ago
(I
don't know whether there is
still
a group who believe this).
Suppose we produce Paul in the flesh. This won't do
-
he is, of course, a cunning
replacement. Suppose we show that no death certificate was issued anywhere around
the time of his purported demise. Well, of course, there was a cover up; it was made
out in a different name. Suppose we supply DNA evidence from the current Paul and
it exactly matches the original Paul's DNA. Another plot; the current sample was
switched behind the scenes
. .
.
and so on. This theory is useless because there is only
(rather stretched) supporting evidence and
no
accepted means of falsification.
Freudian theory often comes under attack for this weakness. Reaction formation can
excuse many otherwise damaging pieces of contradictory evidence. A writer once
explained the sexual symbolism of chess and claimed that the very hostility of chess
players to these explanations was evidence of their validity! They were defending
against the
powefi threat of the nth. Women who claim publicly that they do
not
desire their babies to be male, contrary to 'penis-envy' theory, are reacting internally
against the very real threat that the desire they harbour, originally for their father,
might be exposed, so the argument goes. With this sort of explanation
any
evidence,
desiring males or not desiring them, is taken as support for the theory. Hence, it is
unfalsifiable and therefore untestable in Popper's view.
Conventional scientijZc method
Putting together the empirical method of induction, and the hypothetico-deductive
method, we get what is traditionally taken to be the 'scientific method', accepted by
many psychological researchers as the way to follow in the footsteps of the successful
natural sciences. The steps in the method are shown in Box 1.3.
Box 1.3
Traditional scientific method
I
Observation, gathering and ordering of data
2
Induction of generalisations, laws
3
Development of explanatory theories
4
Deduction
of
hypotheses to test theories
5
Testing of the hypotheses
6
Support or adjustment of theory
Scientific research projects, then, may be concentrating on the early or later stages of
this process. They may be exploratory studies, looking for data from which to create
theories, or they may be hypothesis-testing studies, aiming to support or challenge a
theory.
There are many doubts about, and criticisms of, this model of scientific research,
too detailed to go into here though several aspects of the arguments will be returned
to throughout the book, pamcularly in Chapter 11. The reader might like to consult
Gross (1992) or Valentine (1 992).
MYTH NO.
2:
'SCIENTIFIC RESEARCH INVOLVES DRAMATIC
DISCOVERIES AND BREAKTHROUGHS'
If theory testing was as simple as the dustcart test was, life would produce dramatic
breakthroughs every day. Unfortunately, the classic discoveries are all the lay person
hears about.
In
fact, research plods along all the time, largely according to Figure 1.1.
Although, from reading about research, it
is
easy to think about a single project
beginning and ending at specific points of time, there is, in the research world, a
constant cycle occurring.
A project is developed from a combination of the current trends in research
thinking (theory) and methods, other challenging past theories and,
within
psychol-
ogy at least, from important events in the everyday social world. Tne investigator
might wish to replicate (repeat) a study by someone else in order to venfy it. Or they
The research wroiect
1-
.
,
Analyse Write
Were the aims
1
plan *Implement+-
++
oftheresearch
res,,10
+
repon
-
satisfactorilv met?
findings
important
?
I
I
I
Check design
I
necessary
I
Re-run
I
I
I
Ideas
Replication
Modification
Refutation
Clarification
Events
in
Extension
social world New ground
Modification
It
I
theory
I
I
I
-
Figure
I.
l
The research cycle
might wish to extend it to other areas, or to modify it because it has weaknesses.
Every now and again an investigation breaks completely new ground but the vast
majority develop out of the current state of play.
Politics and economics enter at the stage of funding. Research staff, in universities,
colleges or hospitals, have to justify their salaries and the expense of the project.
~unds
will
come from one of the following: university, college or hospital research
funds; central or local government; private companies; charitable institutions; and
the odd private benefactor. These, and the investigator's direct employers, will need
to be satisfied that the research is worthwhile to them, to society or to the general pool
of scientific knowledge, and that it is ethically sound.
The actual testing or 'running' of the project may take very little time compared
with all the planning and preparation along
with
the analysis of results and report-
writing.
Some procedures, such as an experiment or questionnaire, may be tried out
on a small sample of people in order to highlight snags or ambiguities for which
adjustments can be made before the actual data gathering process is
begun. This is
known as
PILOTING.
The researcher would
run
PILOT
TRIALS
of an experiment or
would
PILOT
a questionnaire, for instance.
The
report will be published in a research journal
if
successful. This term
'successful' is difficult to define here.
It
doesn't always mean that original aims have
been entirely met. Surprises occurring during the research may well make it
important, though usually such surprises would lead the investigator to rethink,
replan and
run
again on the basis of the new insights. As we saw above, failure to
confirm one's hypothesis can be an important source of information. What matters
overall, is that the research results are an important or useful contribution to current
knowledge and theory development. This importance will be decided by the editorial
board of an academic journal (such as the
British
Journal of Psychology)
who
will
have
the report reviewed, usually by experts 'blind' as to the identity of the investigator.
Theory
will
then be adjusted in the light of this research result. Some academics
may argue that the design was so different from previous research that its challenge to
their theory can be ignored. Others will wish-to query the results and may ask the
investigator to provide 'raw data'
-
the whole of the originally recorded data,
unprocessed. Some will want to replicate the study, some to modify
.
.
.
and here we
are, back where we started on the research cycle.
MYTH NO.
3:
'SCIENTIFIC RESEARCH IS ALL ABOUT EXPERIMENTS'
An
experiment involves the researcher's control and manipulation of conditions or
'variables, as we shall see in Chapter
5.
Astronomy, one of the oldest sciences, could not use very many experiments until
relatively recently when technological advances have permitted direct tests of
conditions in space. It has mainly relied upon
obselvation
to test its theories of
planetery motion and stellar organisation.
It is perfectly possible to test hypotheses without an experiment. Much psycho-
logical testing is conducted by observing what children do, asking what people
think
and so on. The evidence about male and female drivers, for instance, was obtained by
observation of actual behaviour and insurance company statistics.
.
'
MYTH NO. 4:-'SCIENTISTS HAVE TO BE UNBIASED'
It
is true that investigators
try
to remove bias from the way a project is
run
and from
the way data is gathered and analysed. But they are biased about theory. They
interpret ambiguous data to fit their particular theory as best they can. This happens
whenever we're in a heated argument and say things like
'Ah,
but that could be
because
. .
.'.
Investigators
believe
in their theory and attempt to produce evidence to
support it. Mitroff (1974) interviewed a group of scientists and all agreed that the
notion of the purely objective, uncornmited scientist was nayve. They argued that:
.
.
.
in order to be a good scientist, one had to have biases. The best
scientist, they said, not only has points of view but also defends them with
gusto. Their concept of a scientist did not imply that he would cheat by
making up experimental data or falsifying it; rather he does everything in
his power to defend his pet hypotheses against early and perhaps unwar-
ranted
death caused by the introduction of fluke data.
DO
WE
GET ON
TO
PSYCHOLOGICAL RESEARCH
NOW?
Yes. We've looked at some common ideas in the language and logic of scientific
research, since most, but not all, psychological investigators would claim to follow a
scientific model. Now let's answer some 'why questions about the practicalities of
psychological research.
WHAT IS THE SUBJECT MATTER FOR PSYCHOLOGICAL RESEARCH?
The easy answer is 'humans'. The more controversial answer is 'human behaviour'
since psychology is literally (in Greek) the study of mind. This isn't a book which will
take you into the great debate on the relationship between mind and body or whether
the study of mind is at all possible. This is available in other general textbooks (e.g.
Gross 1992, Valentine 1992).
Whatever type of psychology you are studying you should be introduced to the
various major 'schools' of psychology (Psycho-analytic, Behaviourist, Cognitive
Humanist,
.
.
.)
It is important to point out here, however, that each school would see
the focus for its subject matter differently
-
behaviour, the conscious mind, even the
unconscious mind. Consequently, different investigatory methods have been devel-
oped by different schools.
Nevertheless, the initial raw data which psychologists gather directly from humans
can
only
be observed behaviour (including physiological responses) or language
(verbal report).
WHY DO PSYCHOLOGISTS DO RESEARCH?
All research has the overall aim of collecting data to expand knowledge. To be
specific, research will usually have one of two major aims: To gather purely
descriptive data or to test hypotheses.
Descriptive research
A
piece of research may establish the ages at which a large sample of children reach
certain language development milestones or it may be a survey (Chapter
8)
of current
adult attitudes to the use of nuclear weapons. If the results from this are in numerical
form then the data are known as
QUANTITATIVE
and we would make use of
DESCRIP~~VE
STATISTICS
(Chapter 13) to present a summary of findings. If the
research presents a report of the contents of interviews or case-studies (Chapter
8),
or
of detailed observations (Chapter
71,
then the data may be largely
QUALITATIVE
(Chapters 4, 11, 25), though parts may well become quantified.
Moving to level
3
of Box 1.3, the descriptive data may well be analysed in order to
generate hypotheses, models, theories or further research directions and ideas.
Hypothesis testing
A
large amount of research sets out to examine one
RESEARCH
HYPOTHESIS
or more by
&owing that differences in relationships between people already exist, or that they
can be created through experimental manipulation.
In
an experiment, the research
hypothesis would be called the
EXPERIMENTAL
HYPOTHESIS. Tests of differences or
relationships between sets of data are performed using
INFERENTIAL
STATISTICS
(Chapters 15-24). Let me describe two examples of
HYPOTHESIS
TESTING,
one
laboratory based, the other from 'the field'.
1
IN
THE
LABORATORY:
A
TEST
OF
SHORT-TERM
MEMORY
THEORY
-
A
theory popular
in the 1960s was the model of short-term (ST) and long-term
(LT)
memory. This
claimed that the small amount of mformation, say seven or eight digits or a few
unconnected words, which we can hold
in
the conscious mind at any one time (our
short-term store) is transferred to a
LT
store by means of rehearsal
-
repetition of
each item in the ST store. The more rehearsal an item received, the better it was
stored and therefore the more easily it was recalled.
A
challenge to this model is that simply rehearsing items is not efficient and rarely
what people actually do, even when so instructed. Humans tend to make incoming
information meaningful. Repetition of words does not, in itself, make them more
meaningful.
An
unconnected list of words
could
be made more meaningful by
forming a vivid mental image of each one and linking it to the next in a bizarre
fashion.
If
'wheel' is followed by 'plane', for instance, imagine
a
candy striped plane
flying through the centre of the previously imaged wheel. We can form the hypothesis
that:
'More items are recalled correctly after learning
by
image-linking than after
learning
by
rehearsal.'
Almost every time this hypothesis is tested with a careful experiment it is clearly
supported by the result. Most people are much better using imagery. This is not the
obvious result it may seem. Many people feel far more comfortable simply repeating
things. They predict that the 'silly' method will confuse them. However, even
if
it
does, the information still sticks better. So, a useful method for exam revision? Well,
making sense of your notes, playing with them, is a lot better than simply reading and
repeating them. Lists of examples can also be stored this way.
2
IN
m
FIEUD:
A
TEST
OF
~TERNAL
DEPR~VATION
-
Bowlby (1951) proposed a
controversial theory that young infants have a natural (that is, biological or innate)
tendency to form a special attachment with just one person, usually the mother,
different in kind and quality from any other.
What does this theory predict? Well, coupled with other arguments, Bowlby was
able to predict that children unable to form such an attachment, or those for whom
this attachment was severed within the first few years of life, especially before three
years old, would later be more likely than other children to become maladjusted.
Bowlby produced several examples of seriously deprived children exhibiting
greater maladjustment. Hence, he could
support
his theory. In this case, he didn't do
something to people and demonstrate the result (which is what an experiment like
14
RESEARCH
&THODS
AND
STATISTICS
IN
PSYCHOLOGY
our memory example above does). He predicted something to be the case, showed it
was, and then related these results back to what had happened to the children in the
past.
But remember that continual support does not
prove
a theory to be correct. Rutter
(1971) challenged the theory with evidence that boys on the Isle of Wight who
suffered early deprivation, even death of their mother, were
not
more likely to be rated
as maladjusted than other boys so long as the separation had not also involved
continuing social difficulties within the family. Here,
Bowlby's theory has to be
adjusted in the light of contradictory evidence.
Hypotheses are
not
aiins
or theories!
Researchers state their hypotheses precisely and clearly. Certain features of the
memory hypothesis above may help you in writing your own hypotheses in practical
reports:
1
No theory is included: we
don't
say, 'People recall more items
because
.
(imagery makes words more meaningful, etc.).
.
.'.
We simply state the
expectation from theory.
2
Effects are precisely defined. We don't say, 'Memory is better
.
.
.',
we define
exactly
how improvement is measured, 'More items are recalled correctly
.
.
.').
In
testing
the hypothesis, we might make the prediction that: 'people
will
recall
significantly more items in the image-linking condition than in the rehearsal
condition'. The term 'significant' is explained in Chapter 14. For now let's just say
we're predicting a difference large enough to be considered
not a fluke.
That is, a
difference that it would rarely occur by chance alone. Researchers would refer, here,
to the 'rejection of the
NULL
HYPOTHESIS'.
The
null
hypothesis
Students always find it odd that psychological researchers emphasise so strongly the
logic of the null hypothesis and its acceptance or rejection. The whole notion is not
simple and has engendered huge, even hostile debate over the years. One reason for
its prominence is that psychological evidence is so firmly founded on the theory of
probability
i.e. decisions about the genuine nature of effects are based on mathemat-
ical
likelihood.
Hence, this concept, too, will be more thoroughly tackled in Chapter
14. For the time being, consider this debate. You, and a friend, have each just bought
a box of matches ('average contents 40'). Being particularly bored or masochistic you
both decide to count them. It turns out that your
fiend has 45 whereas you have a
meagre
36.
'I've been done!' you exclaim, 'just because the newsagent didn't want to
change a E50 note'., Your friend tries to explain that there
will
always be variation
around the average of 40 and that your number is actually closer to the mean than his
is. 'But you've got 9 more than me', you wail. 'Well I'm sure the shopkeeper couldn't
both have it in for you
and
favour me -there isn't time to check
all
the boxes the way
you're suggesting.'
What's happening is that you're making a non-obvious claim about reality,
challenging the status quo, with no other evidence than the matches. Hence, it's
down to you to provide some good 'facts' with which to argue your case. What you
have is a difference
&om the pure average. But is it a difference
large
enough to
convince anyone that it isn't just random variation? It's obviously not convincing
your friend. He is staying with the 'null hypothesis' that the average content really is
40 (and that your difference could reasonably be expected by chance).
Let's look at another field research example. Penny and Robinson (1986)
PSYCHOLOGY
AND
RESEARCH
15
proposed the theory that young people smoke
part&
to reduce stress. Their
hypothesis was that smokers differ from non-smokers on an anxiety measure (the
Spielberger Trait Anxiety Inventory). Note the precision. The
theory
is not in the
hypothesis and the measure of stress is precisely defined. We shall discuss psycho-
logical measures, such as this one, in Chapter 9. The null hypothesis here is that
smokers and non-smokers have a real difference of zero on this scale. Now,
any
test of
two samples
will
always
produce
some
difference, just as any test of two bottles of
washing-~p liquid will inevitably produce a slightly different number of plates washed
successfully. The question is, again, do the groups differ
enough
to reject the status
quo view that they are similar? The notion is a bit like that of being innocent until
proved
gulty.
There's usually
some
sort of evidence against an accused but
if
it isn't
strong enough we stick, however uncomfortably, to the innocent view. This doesn't
mean that researchers
give
up nobly. They often talk of 'retaining' the nd
hypothesis. It will not therefore be treated as
true.
In
the case above the null
hypothesis was rejected
-
smokers scored significantly higher on
this
measure of
anxiety. The result therefore supported the researchers'
ALTERNATIVE
HYPOTHESIS.
In
the maternal deprivation example, above, we can see that after testing, Rutter
claimed the null hypothesis (no difference between deprived and non-deprived boys)
could
not
be rejected, whereas Bowlby's results had been used to
support
rejection.
A
further cross-cultural example is given by Joe (1991) in Chapter 10. Have a look at
the way we might use the logic of null hypothesis
thinking
in everyday life, as
described in Box 1.4.
Box 1.4
The null hypothesis
-
the truth standing on
its
head
-
-
,
Everyday
thinking
:
Women just don't have a chance of
1
managemeat promotion
in
this pla5e.
In
the
I
last four intkrviews they picked a male each
!
time out of a shortlist of two females and
'
two males
Really?
Let's see, how many males should
,
they have selected
if
you're wrong?
:
How do ?ou mean?
Well, there were the same number of
;
female as male candidates each time, so
there should have been just asmany
females
as
males selected
in
all. That's two!
'
Oh yeah! That's what
l
meant to
start
with.
There should have been at
least
two new
%
.
women managers from that round of
,
selection
,
Well just two unless we're compensating
forpast male advantage! Now is none out
,
of four different enough from two out of
I
four to give us hard evidence of selection
,
bias?
Formal research
thinking
Hypothesis of interest: more males get
selected for- management
Construct
null
hypothesis
-
what would
happen
if
our theory is not true?
Express the null hypothesis statistically. Very
often this is that the difference betwe
n
the
9.
two sets of scores is really zero. Here,
~t
1s
that the difference%etween females and
males selected will be zero
Note: if there had been three female
candidates and only one male each time,
the
null
hypothesis would predict three
females selected
in
all
Conduct a statistical test to assess the
probability that the actual figures would
differ as much
as
they do from what the
null
hypothesis predicts
Directional and non-directional hypotheses
If
smokers use cigarettes to reduce stress you might argue that, rather than finding
them
higher
on anxiety, they'd be
lower
-
so long as they had a good supply! Hence,
Penny and Robinson could predict that smokers might be higher
or
lower than non-
smokers on anxiety. The hypothesis would be known as
c~~~-~~~~~~~~~~'
(some
say 'two-sided' or 'two-tailed')
-
where the direction of effect is -not predicted. A
DmxnoNAL hypothesis
does
predict the direction e.g., that people using imagery
will
recall
more
words. Again, the underlying notion here is statistical and will be dealt
with
more fully in Chapter 14.
When
is
a
hypothesis test Csuccessficl'?
The decision is based entirely on a
TEST
OF
SIGNIFICANCE,
which estimates the
unlikelihood of the obtained results occurring
if
the null hypothesis is true. We
will
discuss these in Chapter 14. However, note that, as with Rutter's case, a demonstra-
tion of no real difference can be very important. Although young women consistently
rate
their
IQ
lower than do young men, it's important to demonstrate that there is, in
fact, no real difference in
IQ.
Students doing practical work often get quite despondent when what they
predicted does not occur. It feels very much as though the project hasn't worked.
Some students
I
was teaching recently failed to show, contrary to their expectations,
that the 'older generation' were more negative about homosexuality than their own
generation.
I
explained that it was surely important information that the 'older
generation' were just as liberal as they were (or, perhaps, that their generation were
just as hostile).
If hypothesis tests 'fail' we either accept the null hypothesis as important
information or we critically assess the design of the project and look for weaknesses in
it. Perhaps we asked the wrong questions or the wrong people? Were instructions
clear enough? Did we test everybody fairly and in the same manner? The process of
evaluating our design and procedure is educational in itself and forms an important
part of our research report
-
the 'Discussion'. The whole process of writing a report is
outlined in Chapter 28.
HOW DO PSYCHOLOGISTS CONDUCT RESEARCH?
A
huge question and basically an introduction to the rest of the book! A very large
number of psychologists use the experimental method or some form of well
controlled careful investigation, involving careful measurement in the data gathering
process.
In
Chapter 11, however, we shall consider why a growing number of psychologists
reject the use of the experiment and may also tend to favour methods which gather
qualitative data
-
information from people which is in descriptive, non-numerical,
form. Some of these psychologists also reject the scientific method as
I
have outlined
it. They accept that this has been a successful way to study inert matter, but seek an
alternative approach to understanding ourselves. Others reinterpret 'science' as it
applies to psychology.
One thing we can say, though, is, whatever the outlook of the researcher, there are
three major ways to get information about people. You either ask them, observe them
or meddle. These are covered in 'Asking questions', 'Observational methods' and
'The experimental method @art
1
and part 2)'.
TO
get us started, and to allow me to introduce the rest of this book, let's look at the
key decision areas facing anyone about to conduct some research.
I
have identified
these in Figure 1.2. Basically, the four boxes are answers to the questions:
variables: WHAT shall we study? (what human characteristics under what
conditions?)
Design:
HOW shall we study these?
Samples: WHO shall we study?
Analysis:
WHAT sort of evidence will we get, in what form?
VARIABLES
Variables are tricky things. They are the things which alter so that we can make
comparisons, such as 'Are you tidier than I
am?'
Heat is a variable in our study. How
shall we define it? How shall we make sure that it isn't humidity, rather than
temperature, that is responsible for any irritability?
But the real problem is how to measure 'irritability'. We could, of course, devise
some sort of questionnaire. The construction of these is dealt with in Chapter
9.
We
could observe people's behaviour at work on hot and cool days. Are there more
arguments? Is there more swearing or shouting? We could observe these events in the
street or in some families. Chapter
7
will deal
with
methods of observation.
We could even bring people into the 'laboratory' and see whether they tend to
answer our questionnaire differently under a well-controlled change in temperature.
We could observe their behaviour whilst carrying out a frustrating task (for instance,
balancing pencils on a slightly moving surface) and we could ask them to assess this
task under the two temperature conditions.
The difficulty of defining variables, stating exactly what it is we mean by a term
and how,
if
at all, we intend to measure it, seemed to me to be so primary that
I
gave
it the first chapter in the main body of the book (Chapter 2).
Variables
Q
Design
I
+
PLAN
Samples
<
Analysis
Figure
1.2
Key decision areas in research
18
RESEARCH
METHODS
AND
STATISTICS
IN
PSYCHOLOGY
DESIGN
The decisions about variable measurement have taken us into decisions about the
DESIGN.
The design is the overall structure and strategy of the research. Decisions on
measuring irritability may determine whether we conduct a laboratory study or 'field'
research.
If
we want realistic irritability we might wish to measure it as it occurs
naturally, 'in the field'. Ifwe take the laboratory option described above, we would be
running an experiment. However, experiments can be run using various designs.
Shall we, for instance, have the same group of people perform the frustrating task
under the two temperature conditions? If so, mighm't they be getting practice at the
task which will make changes in their performance harder to interpret? The variety of
experimental designs is covered in Chapter 6.
There are several constraints on choice of design:
1
RESOURCES -The researcher may not have the funding, staff or time to carry out a
long-term study. The most appropriate technical equipment may be just too
expensive. Resources may not stretch to testing in different cultures.
A
study in the
natural setting
-
say in a hospital -may be too time consuming or ruled out by lack of
permission. The laboratory may just have to do.
2 NATURE
OF
RESEARCH
ALM
-
If the researcher wishes to study the effects of
maternal deprivation on the three-year-old, certain designs are ruled out. We can't
experiment by artificially depriving children of their mothers
(I
hope you agree!) and
we can't question a three-year-old in any great depth. We may be left with the best
option of observing the child's
behaviour, although some researchers have turned to
experiments on animals in lieu of humans. The ethics of such decisions are discussed
more fully in Chapter 26.
3 PREVIOUS
RESEARCH
-
If we intend to repeat an earlier study we must use the same
design and method.
An
extension of the study may require the same design, because
an extra group is to be added, or it may require use of a different design which
complements the first. We may wish to demonstrate that a laboratory discovered
effect can be reproduced in a natural setting, for instance.
4
THE
RESEARCHER'S
A~E
TO
SCIENTIFIC
INVESTIGATION
-
There can be hostile
debates between psychologists from Merent research backgrounds. Some swear by
the strictly controlled laboratory setting, seeking to emulate the 'hard' physical
sciences in their isolation and precise measurement of variables. Others prefer the
more realistic 'field' setting, while there is a growing body of researchers with a
humanistic, 'action research' or 'new paradigm' approach who favour qualitative
methods. We shall look more closely at this debate in the methods section.
SAMPLES
These are the people we are going to study or work with. If we carry out our field
observations on office workers (on hot and cool days) we might be showing only that
these sort of people get more irritable in the heat. What about builders or nurses? If
we select a sample for our laboratory experiment, what factors shall we take into
account in trying to make the group representative of most people
in
general? Is this
possible? These are issues of 'sampling' and are dealt with in Chapter
3.
One word on terminology here. It is common to refer to the people studied in
psychological research, especially in experiments, as 'subjects'. There are objections
to this, particularly by psychologists who argue that a false model of the human being
1
PSYCHOLOGY
AND
RESEARCH
19
4
is generated by referring to (and possibly treating) people studied
in
this
distant,
5.
rnollv scientific manner. The British Psychological Society's rRevised Ethical Princi-
<
pies
for Conducting Research with I3uman Participants' were in provisional opera-
;F
tion from February 1992. These include the principle that, on the grounds of
owesy and gratitude to participants, the terminology used about them should carry
4
obvious respect (although traditional psychologists did not intend 'subjects' to be
derogatory). The principles were formally adopted in October 1992. However,
1
z
through 1992 and up to mid-1993, in the British Journal
of
Psychology, there was only
one use of 'participants' in over 30 research reports, so we are in a transition phase on
this term.
-
Some important terminology uses 'subject', especially 'subject variables' (Chapter
!
31,
md 'between' or 'within subjects' (Chapters 20-22).
In
the interest of clarity I
have included both terms in Chapter 3 but stuck to the older one in Chapters 20-22
in
order not to confuse readers checking my text
with
others on a difficult statistical
topic. Elsewhere, in this second edition, you should iind that 'subjects' has been
i
7.
purged except for appearances in quotes.
;'
ANALYSIS
The design chosen, and method of measuring variables,
will
have a direct effect on
the statistical or other analysis which is possible at the end of data collection.
In
a
straightforward hypothesis-testing study, it is pointless to steam ahead with a design
and procedure, only to find that the results can barely be analysed in order to support
the hypothesis.
There is a principle relating to computer programming which goes: 'garbage in
-
garbage out'. It applies here too. If the questionnaire contains items like 'How do you
feel?', what is to be done
with
the largely unquantifiable results?
Thoughts of the analysis should not stifle creativity but it is important to keep it
central to the planning.
!
ONE LAST WORD ON THE NATURE OF SCCENTlFlC RESEARCH (FOR
NOW
Throughout the book, and in any practical work, can I suggest that the reader keep
i
the following words fiom Rogers (1961) in mind?
If
taken seriously to heart and
c
practised, whatever the arguments about various methods,
I
don't
think
the follower
-
of this idea
will
be far away from 'doing science'.
Scientific research needs to be seen for what it truly is; a way of preventing
me from deceiving myself in regard to my creatively formed subjective
hunches which have developed out of the relationship between me and my
material.
r
Note:
at the end of each chapter in this book there is a set of definitions for terms
introduced. If you want to use this as a self test, cover up the right-hand column. You
can then write in your guess as to the term being defined or simply check after you
c
read each one. Heavy white lines enclose a set of similar terms, as with the various
types of hypotheses, overleaf.
I
!
