Research Methods and Statistics in Psychology

245 Pages · 2006 · 24.63 MB · English

  • Research Methods and Statistics in Psychology

    Research Methods and Statistics in



    Hugh Coolican


    Hodder & Stoughton

    A MEMBER OF THE HODDER HEADLINE GROUP Preface to the first edition xi

    Preface to the second edition xii

    PART I Introduction 1

    Chapter 1 Psychology and research 3

    Scientific research; empirical method; hypothetico-deductive method;

    falsifiability; descriptive research; hypothesis testing; the null-hypothesis;

    one- and two-tailed hypotheses; planning research.

    Chanter 2 Variables and definitions 22

    Psychological variables and constructs; operational definitions;

    independent and dependent variables; extraneous variables; random and

    constant error; confounding.

    Chapter 3 Samples and groups 34

    Populations and samples; sampling bias; representative samples; random

    samples; stratified, quota, cluster, snowball, self-selecting and

    opportunity samples; sample size. Experimental, control and placebo


    PART ll Methods 47

    Chapter ,4 Some general themes 49

    Reliability. Validity; internal and external validity; threats to validity;

    ecological validity; construct validity. Standardised procedure; participant

    variance; confounding; replication; meta-analysis. The quantitative-

    qualitative dimension.

    Chapter 5 The experimental method I: nature of the method 66

    Expeiiments; non-experimental work; the laboratory; field experiments;

    quasi-experiments; narural experiments; ex post facto research; criticisms

    of the experiment.

    Chapter 6 The experimental method U: experimental designs 81

    Repeated measures; related designs; order effects. Independent samples

    design; participant (subject) variables. Matched pairs. Single participant. Chavter 7 Observational methods Chapter 14 Probability and significance

    Observation as technique and design; participant and non-participant Logical, empirical and subjective probability; probability distributions.

    observation; structured observation; controlled observation; naturalistic Significance; levels of significance; the 5% level; critical values; tails of

    observation-; obj.ecti ons to structured observation; aualitative non- distributions; the normal probability distribution; significance of z-scores;


    participant observation; role-play and simulation; the e diary method; importance of 1% and 10% levels; type I and type I1 errors.

    participant observation; indirect observation; content analysis; verbal

    protocols. Section 2 Simple tests of difference - non-parametric

    Using tests of significance - general procedure

    Chapter 8 Asking questions I: interviews and surveys

    Structure and disguise; types of interview method; the clinical method; Chapter 15 Tests at nominal level

    the individual case-study; interview techniques; surveys. Binomial sign test. Chi-square test of association; goodness of fit; one

    variable test; limitations of chi-square.

    Chapter 9 Asking questions 11: questionnaires, scales and tests

    Questionnaires; attitude scales; questionnaire and scale items; projective Chapter 16 Tests at ordinal level

    tests; sociomeny; psychometric rests. Reliability, validity and Wilcoxon signed ranks. Mann-Whitney U. Wilcoxon rank sum. Testing

    standardisation of tests. when N is large.

    Chapter 10 Comparison studies Section 3 Simple tests of dzfference -parametric

    Cross-sectional studies; longitudinal studies; short-term longitudinal

    studies. Cross-cultural studies; research examples; indigenous Chapter 17 Tests at internayratio level

    psychologies; ethnicity and culture within one society. Power; assumptions underlying parametric tests; robustness. t test for

    related data; t test for unrelated data.

    Chapter 11 New paradigms

    Positivism; doubts about positiyism; the establishment paradigm; Section 4 Correlation

    objections to the traditional paradigm; new paradigm proposals;

    qualitative approaches; feminist perspective; discourse analysis; Chapter 18 Correlation and its significance

    reflexivity. The nature of correlation; measurement of correlation; scattergrams.

    Calculating correlation; Pearson's product-moment coefficient;

    Spearman's Rho. Significance and correlation coefficients; strength and

    significance; guessing error; variance estimate; coefficient of

    PART Ill Dealing with data

    determination. What you can't assume with a correlation; cause and

    effect assumptions; missing middle; range restriction; correlation when

    Chapter 12 Measurement

    one variable is nominal; general restriction; dichotomous variables and

    Nominal level; ordinal level; interval level; plastic interval scales; ratio

    the point biserial correlation; the Phi coefficient. Common uses of

    level; reducing from interval to ordinal and nominal level; categorical and

    correlation in psychology.

    measured variables; continuous and discrete scales of measurement.

    Section 5 Tests for more than two conditions

    Chapter 13 Descriptive statistics

    Introduction to more complex tests

    Central tendency; mean; median; mode. Dispersion; range; serni-

    interquartile range; mean deviation; standard deviation and variance.

    Chapter 19 Non-parametric tests -more than two conditions

    Population parameters and sample statistics. Distributions; percentiles;

    Kruskal-Wallis (unrelated differences). Jonckheere (unrelated trend).

    deciles and quades. Graphical representation; histogram; bar chart;

    Friedman (related differences). Page (related trend).

    frequency polygon; ogive. Exploratory data analysis; stem-and-leaf

    display; box plots. The normal distribution; standard (z-) scores; skewed

    distributions; standardisation of psychological measurements.

    Chapter 20 One way ANOVA

    Comparing variances; the F test; variance components; sums of squares;

    calculations for one-way; the significance and interpretation of F. A priori

    PART IV Using data to test predictions and'post hoc comparisons; error rates; Bonferroni t tests; linear contrasts

    and coefficients; Newman-Keuls; Tukey's HSD; unequal sample

    Section 1 An introduction to sipificance testing numbers. Chapter 2 1 Multi-factor ANOVA

    Factors and levels; unrelated and related designs; interaction effects;

    main effects; simple effects; partitioning the sums of squares; calculation

    for two-way unrelated ANOVA; three-way ANOVA components. After the domination of behaviourism in Anglo-American psychology during the

    middle of the century, the impression has been left, reflected in the many texts on

    Chapter 22 Repeated measures ANOVA research design, that the experimental method is the central tool of psychological

    Rationale; between subjects variation; division of variation for one-way research. In fact, a glance through journals will illuminate a wide array of data-

    repeated measures design; calculation for one-way design; two-way gathering instruments in use outside the experimental laboratory and beyond the

    related design; mixed model - one repeat and one unrelated factor; field experiment. This book takes the reader through details of the experimental

    division of variation in mixed model. method, but also examines the many criticisms of it, in particular the argument that

    its use, as a paradigm, has led to some fairly arid and unrealistic psychological

    Chapter 23 Other useful complex multi-variate tests - a brief summary models, as has the empirical insistence on quantification. The reader is also

    MANOVA, ANCOVA; multiple regression and multiple predictions. introduced to non-experimental method in some depth, where current A-level texts

    tend to be rather superficial. But, further, it takes the reader somewhat beyond

    Section 6 What analysis to use? current A-level minimum requirements and into the world of qualitative


    Chapter 24 Choosing an appropriate test Having said that, it is written at a level which should feel 'friendly' and comfortable

    Tests for two samples; steps in making a choice; decision chart; examples to the person just starting their study of psychology. The beginner will find it useful to

    of choosing a test; hints. Tests for more than two samples. Some read part one first, since this section introduces fundamental issues of scientific

    information on computer programmes. method and techniques of measuring or gathering data about people. Thereafter, any

    reader can and should use it as a manual to be dipped into at the appropriate place for

    Chapter 25 Analysing qualitative data the current research project or problem, though the early chapters of the statistics

    Qualitative data and hypothesis testing; qualitative analysis of qualitative section will need to be consulted in order to understand the rationale and procedure

    content; methods of analysis; transcribing speech; grounded theory; the of the tests of significance.

    final report. Validity. On doing a qualitative project. Analysing discourse. I have med to write the statistical sections as I teach them, with the mathematically

    Specialist texts. nervous student very much in mind. Very often, though, people who think they are

    poor at mathematical thinking find statistics far less diicult than they had feared,

    PART V Ethics and practice and the tests in this book which match current A-level requirements involve the use of

    very few mathematical operations. Except for a few illuminative examples, the

    Chapter 26 Ethical issues and humanism in psychological research statistical concepts are all introduced via realistic psychological data, some emanating

    Publication and access to data; confidentiality and privacy; the Milgram fkom actual studies performed by students.

    experiment; deception; debriefing; stress and discomfort; right to non- This book will provide the A-level, A/S-level or International Baccalaureate

    participation; special power of the investigator; involuntary participation; student with all that is necessary, not only for selecting methods and statistical

    intervention; research with animals. treatments for practical work and for structured questions on research examples, but

    also for dealing with general issues of scientific and research methods. Higher

    Chapter 27 Planning practicals education students, too, wary of statistics as vast numbcrs of psychology beginners

    often are, should also find this book an accessible route into the area. Questions

    Chapter 28 Writing your practical report , throughout are intended to engage the reader in active thinking about the current

    topic, often by stimulating the prediction of problems before they are presented. The

    Appendix 1 Structured questions final structured questions imitate those found in the papers of several Examination

    Appendix 2 Statistical tables Boards.

    Appendix 3 Answers to exercises and structured questions I hope, through using this book, the reader will be encouraged to enjoy research;

    not to see it as an inrirnidating add-on, but, in fact, as the engine of theory without


    References which we would be left with a broad array of truly fascinating ideas about human

    experience and behaviour with no means of telling which are sheer fantasy and which

    Index might lead us to models of the human condition grounded in reality.

    If there are points in this book which you wish to question, please get in touch via

    f the publisher.

    Hugh Coolican

    i P A R T O N E

    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 Introduction

    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-


    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 This introduction sets the scene for research in psychology. The key ideas are


    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


    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 h em aths 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 I have used these statements, including the controversial ones, because they are just

    in your head in an informal way, even 'hard' topics like probability. My job is to the sort of things people claim confidently, yet with no hard evidence. They are

    give names to some concepts you will easily think of for yourself. At other times it will

    'hunches' masquerading as fact. I call them 'armchair certainties (or theories)'

    be to formalise and tighten up ideas that you have gathered through experience. For

    because this is where they are often claimed from.

    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

    Box I. I 'Common-sense' claims

    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. 1 Women obviously have a maternal Have we checked how men would feel

    instinct - look how strongly they want to after several months alone with a baby?

    Returning to the prospective student then, he or she usually has little clue about

    stay with their child and protect it Does the tern 'instinct' odd to our

    what sort of research psychologists do. The notion of 'experiments' sometimes

    understanding, or does it simply describe

    produces anxiety. 'Will we be conditioned or brainwashed?'

    If we ignore images from the black-and-white film industry, and think carefully what mothers do and, perhaps, feel? Do all

    mothers feel this way?

    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 2 Michelle is so good at predicting people's Have we checked that Michelle gets a lot

    behaviour. I agree with Gross (1992) who says that, at a party, if one admits to star sign -there must be something in more signs correct than anyone would by

    teaching, or even studying, psychology, a common reaction is 'Oh, I'd better be astrology just guessing? Have we counted the times

    careful what I say from now on'. Another strong contender is 'I suppose you'll be when she's wrong?

    analysing my behaviour' (said as the speaker takes one hesitant step backwards) in the 3 So many batsmen get out on 98 or 99 - Have we compared with the numbers of

    mistaken assumption that psychologists go around making deep, mysterious inter- it must be the psychological pressure batsmen who get out on other high totals?

    pretations of human actions as they occur. (If you meet someone who does do this, 4 Women are less logical, more suggestible Women score the same as men on logical -

    ask them something about the evidence they use, after you've finished with this

    and make worse drivers than men tests in general. They are equally

    book!) The notion of such analysis is loosely connected to Freud who, though

    'suggestible', though boys are more likely to

    popularly portrayed as a psychiatric Sherlock Holmes, used very few of the sorts of

    agree with views they don't hold but which

    research outlined in this book - though he did use unstructured clinical interviews

    are held by their peer group. Statistically,

    and the case-study method (Chapter 8).

    women are more -likely to obey traffic rules

    and have less expensive accidents. Why else

    SO 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

    Although there are endless and furious debates about what a science is and what son

    had fallen silent after screaming horribly

    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, 6 The trouble with having so many black In 199 I, the total black population of the

    controlled and checkable. There is no final agreement, however, about precisely how immigrants is that the country is too UK (African Caribbean and Indian sub-

    scientific method should operate within the very broad range of psychological small' (Quote from Call Nick Ross phone- continental Asian) was a little under 5%.

    research topics. There are many definitions of science but, for present purposes, in, BBC Radio 4,3.1 1.92) Almost every year since the second world

    Allport's (1 947) is useful. Science, he claims, has the aims of: war, more people haye left than have

    entered Britain to live. Anyway, whose

    '. . . 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 I hope you see why we need evidence from research. One role for a scientific study is

    instance? Let's have a look at some other popular 'common-sense' claims. 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

    fa 30-metre-tall Maman made empirical observations on Earth, it (Martians have

    scientific research is by dispelling a few myths about it.

    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.

    All research is about the collection of data but this is not the sole aim. First of all, facts The Martian might then conclude that the tubes were important life-forms and

    are not data. Facts do not speak for themselves. When people say they do they are that the little bugs taken on were food . . . and the ones discharged . . . ?

    omitting to mention essential background theory or assumptions they are making. 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

    A sudden crash brings us running to the kitchen. The accused is crouched

    forces or processes underly them.

    in front of us, eyes wide and fearful. Her hands are red and sticky. A knife

    It is inevitable that human thinking will go beyond the patterns and combinations

    lies on the floor. So does a jam jar and its spilled contents. The accused

    discovered in data analysis to ask, 'But why?'. It is also naive to assume we could ever

    was about to lick her tiny fingers.

    gather data without some background theory in our heads, as I tried to demonstrate

    I hope you made some false assumptions b'efore the jam was mentioned. But, as it is, above. Medawar (1963) has argued this point forcefully, as has Bruner who points

    do the facts alone tell us that Jenny was stealing jam? Perhaps the cat knocked the jam out that, when we perceive the world, we always and inevitably 'go beyond the

    over and Jenny was trying to pick it up. We constantly assume a lot beyond the information given'.

    present data in order to explain it (see Box 1.2). Facts are DATA interpreted through -

    THEORY. Data are what we get through EMP~CALo bservation, where 'empirical' Testing theories the hypothetico-deductive method

    refers to information obtained through our senses. It is difficult to get raw data. We This Martian's theory, that the bugs are food for the tubes, can be tested. If the tubes

    almost always interpret it immediately. The time you took to run 100 metres (or, at get no bugs for a long time, they should die. This prediction is a HYPOTHESIS. A

    least, the position of the watch hands) is raw data. My saying you're 'quickJ is hypothesis is a statement of exactly what should be the case $a certain theory is true.

    interpretation. If we lie on the beach looking at the night sky and see a 'star' moving Testing the hypothesis shows that the tubes can last indefinitely without bugs. Hence

    steadily we 'know' it's a satellite, but only because we have a lot of received the hypothesis is not supported and the theory requires alteration or dismissal. This

    astronomical knowledge, from our culture, in our heads. manner of thinking is common in our everyday lives. Here's another example:

    Box 1.2 Fearing or clearing the bomb? 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

    In psychology we conbntly challenge the simplistic acceptance of fa& 'in front of our

    , let's check next Tuesday. They're coming a day later next week because

    eyes'. A famous bomb disposal officer, talking to Sue Lawley on Desert lslond Discs, told of

    there's a Bank Holiday.'

    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, The logic here is essential to critical thinking in psychological research.


    'terrified member of public flees bomb', whereas another paper correctly identified him as The theory investigated is that the dustcart knocks the mirror.

    the calm, but concerned expert he really was.

    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.

    Data are interpreted through what psychologists often call a 'schema' - our learned

    * If the mirror is knocked the theory is supported.

    prejudices, stereotypes and general ideas about the world and even according to our

    If the mirror is not knocked the theory appears wrong.

    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 Notice, we say only 'supported' here, not 'proven true' or anything definite like that.

    psychological truth, most researchers share common ground in following some basic This is because there could be an alternative reason why it got knocked. Perhaps the

    principles of contemporary science which date back to the revolutionary use of boy who follows the cart each week on his bike does the knocking. This is an example

    EMPIRICAL METHOD to start questioning the workings of the world in a consistent of 'confounding' which we'll meet formally in the next chapter. If you and your friend

    manner. 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

    The empirical method


    The original empirical method had two stages: We say 'supported' then, rather than 'proved', because D (the dustcart) might not

    1 Gathering of data, directly, through our external senses, with no preconceptions have caused M (mirror getting knocked) - our theory. Some other event may have

    as to how it is ordered or what explains it. 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

    2 IN~ucnoNof patterns and relationships within the data.

    might think that a blown fuse caused damage to your washing machine, which now

    'Induction' means to move &om individual observations to statements of general won't run, when actually the machine broke, overflowed and caused the fuse to blow.

    patterns (sometimes called 'laws'). 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 evidence. There is often a balance in favour with several anomalies yet

    theory, that girls are more talkative because their mothers talk more to them are both to explain. Theories tend to 'survive' or not against others depending on the quality,

    supported by the evidence that mothers do talk more to their daughters. Evidence is not just the quantity, of their supporting evidence. But for every single supportive

    more useful when it supports one theory and not its rival. piece of evidence in social science there is very often an alternative explanation. It

    Ben Elton (1989) is onto this when he says: might be claimed that similarity between parent and child in intelligence is evidence

    for the view that intelligence is genetically transmitted. However, this evidence

    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 supports equally the view that children learn their skills from their parents, and

    much more sense to say 'no wonder half of them are piss-heads, they're so - similarity between adoptive parent and child is a challenge to the theory.

    poor'. Fakz3a bility

    Deductive logic popper (1959) has argued that for any theory to count as a theory we must at least be

    Theory-testing relies on the logical arguments we were using above. These are able to see how it could be falsified -we don't have to be able to falsify it; after all, it

    examples of DEDUCTION. Stripped to their bare skeleton they are: 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

    Applied to the0y -testing Applied to the dustcart and

    replacement. Suppose we show that no death certificate was issued anywhere around

    mirror problem

    1 If X is true then Y must 1 If theory A is true, then 1 If the dustcart knocks the time of his purported demise. Well, of course, there was a cover up; it was made

    be true hypothesis H will be the mirror then the mir- 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

    coniirmed ror will get knocked

    switched behind the scenes . . . and so on. This theory is useless because there is only

    next Tuesday

    2 Y isn't true 2 H is disconfinned 2 The mirror didn't get (rather stretched) supporting evidence and no accepted means of falsification.

    Freudian theory often comes under attack for this weakness. Reaction formation can


    3 Therefore X is not true 3 Theory A is wrong* 3 Therefore it isn't the 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

    or or

    against the powefi threat of the nth. Women who claim publicly that they do not

    2 Yistrue 2 H is coniirmed 2 The mirror did get

    desire their babies to be male, contrary to 'penis-envy' theory, are reacting internally


    3 X could still be true 3 Theory A could be true 3 Perhaps it is the dust- 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.

    *At this point, according to the 'official line', scientists should drop the theory with

    Conventional scientijZc method

    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 Putting together the empirical method of induction, and the hypothetico-deductive

    because of a 'hunch' that the data were wrong. This hunch was sometime shown to method, we get what is traditionally taken to be the 'scientific method', accepted by

    be correct. The beauty of a theory can outweigh pure logic in real science practice. 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.

    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

    Box 1.3 Traditional scientific method

    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.

    I Observation, gathering and ordering of data

    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 2 Induction of generalisations, laws

    would have to adjust your theory to take account of new data. For instance, your 3 Development of explanatory theories

    friend might have a smug look on her face. 'Did you know it was the Council's "be-

    4 Deduction of hypotheses to test theories

    ever-so-nice-to-our-customers" promotion week and the collectors get bonuses if

    5 Testing of the hypotheses

    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 6 Support or adjustment of theory

    external events as constant as possible. 'Never mind,' your fiend soothes, 'we can

    always write this up in our psychology essay on scientific method'. Scientific research projects, then, may be concentrating on the early or later stages of

    Theories in science don't just get 'proven true' and they rarely rest on totally 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 might wish to extend it to other areas, or to modify it because it has weaknesses.

    theory. Every now and again an investigation breaks completely new ground but the vast

    There are many doubts about, and criticisms of, this model of scientific research, majority develop out of the current state of play.

    too detailed to go into here though several aspects of the arguments will be returned Politics and economics enter at the stage of funding. Research staff, in universities,

    to throughout the book, pamcularly in Chapter 11. The reader might like to consult colleges or hospitals, have to justify their salaries and the expense of the project.

    Gross (1992) or Valentine (1 992). ~undws ill come from one of the following: university, college or hospital research

    funds; central or local government; private companies; charitable institutions; and

    MYTH NO. 2: 'SCIENTIFIC RESEARCH INVOLVES DRAMATIC the odd private benefactor. These, and the investigator's direct employers, will need

    DISCOVERIES AND BREAKTHROUGHS' 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.

    If theory testing was as simple as the dustcart test was, life would produce dramatic

    The actual testing or 'running' of the project may take very little time compared

    breakthroughs every day. Unfortunately, the classic discoveries are all the lay person

    with all the planning and preparation along with the analysis of results and report-

    hears about. In fact, research plods along all the time, largely according to Figure 1.1.

    writing. Some procedures, such as an experiment or questionnaire, may be tried out

    Although, from reading about research, it is easy to think about a single project

    on a small sample of people in order to highlight snags or ambiguities for which

    beginning and ending at specific points of time, there is, in the research world, a

    adjustments can be made before the actual data gathering process is begun. This is

    constant cycle occurring.

    known as PILOTING. The researcher would run PILOT TRIALS of an experiment or

    A project is developed from a combination of the current trends in research

    would PILOT a questionnaire, for instance.

    thinking (theory) and methods, other challenging past theories and, within psychol-

    The report will be published in a research journal if successful. This term

    ogy at least, from important events in the everyday social world. Tne investigator

    'successful' is difficult to define here. It doesn't always mean that original aims have

    might wish to replicate (repeat) a study by someone else in order to venfy it. Or they

    been entirely met. Surprises occurring during the research may well make it

    important, though usually such surprises would lead the investigator to rethink,

    The research .w roiect 1- replan and run again on the basis of the new insights. As we saw above, failure to

    1 ,

    Were the aims confirm one's hypothesis can be an important source of information. What matters

    Analyse Write

    plan *Implement+- res,,10 + repon ++ oftheresearch overall, is that the research results are an important or useful contribution to current

    - satisfactorilv met? 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

    findings their theory can be ignored. Others will wish-to query the results and may ask the

    important ? 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.




    I Check design

    An experiment involves the researcher's control and manipulation of conditions or

    I necessary 'variables, as we shall see in Chapter 5.

    I Re-run 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.

    I t

    I It is perfectly possible to test hypotheses without an experiment. Much psycho-

    I Ideas

    logical testing is conducted by observing what children do, asking what people think

    Replication Modification

    and so on. The evidence about male and female drivers, for instance, was obtained by


    Refutation - observation of actual behaviour and insurance company statistics. . '



    Events in Extension theory I MYTH NO. 4:-'SCIENTISTS HAVE TO BE UNBIASED'

    social world New ground

    I I It is true that investigators try to remove bias from the way a project is run and from

    Figure I. l The research cycle the way data is gathered and analysed. But they are biased about theory. They

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