Research Methods for Postgraduates (eBook)

Tony Greenfield, Sue Greener (Herausgeber)

eBook Download: EPUB

2016 | 3. Auflage
John Wiley & Sons (Verlag)
978-1-118-76299-8 (ISBN)

Infos

An indispensable reference for postgraduates, providing up to date guidance in all subject areas

Methods for Postgraduates brings together guidance for postgraduate students on how to organise, plan and do research from an interdisciplinary perspective. In this new edition, the already wide-ranging coverage is enhanced by the addition of new chapters on social media, evaluating the research process, Kansei engineering and medical research reporting. The extensive updates also provide the latest guidance on issues relevant to postgraduates in all subject areas, from writing a proposal and securing research funds, to data analysis and the presentation of research, through to intellectual property protection and career opportunities.

 This thoroughly revised new edition provides:

• Clear and concise advice from distinguished international researchers on how to plan, organise and conduct research.
• New chapters explore social media in research, evaluate the research process, Kansei engineering and discuss the reporting of medical research.
• Check lists and diagrams throughout. 

Praise for the second edition:

'... the most useful book any new postgraduate could ever buy.' (New Scientist)
'The book certainly merits its acceptance as essential reading for postgraduates and will be valuable to anyone associated in any way with research or with presentation of technical or scientific information of any kind.'(Robotica)

 Like its predecessors, the third edition of Research Methods for Postgraduates is accessible and comprehensive, and is a must-read for any postgraduate student.

Editors:Tony Greenfield, Industrial Statistics Research Unit (ISRU), University of Newcastle-upon-Tyne, UK; and Sue Greener, Brighton Business School, Brighton, UK

Inhalt

About the Author ix

List of Contributors xi

Preface to the Third Edition xiii

Preface to the Second Edition xix

Preface to the First Edition xxi

Part I First Steps 1

1 A View of Research 3
Tony Greenfield

2 The Research Journey: Four Steps to Success 7
Tom Bourner and Sue Greener

3 Managing Your Doctorate 13
Stan Taylor

4 Documenting Your Work 34
Vivien Martin

5 Ethics of Research 46
Tony Greenfield

6 Plagiarism 56
Tony Greenfield

7 Critically Reviewing Your Own Research 60
Tom Bourner and Juliet Millican

Part II Support 69

8 Research Proposals for Funding 71
Lowry McComb

9 Who Can Help? 81
Shirley Coleman

10 Information and Library Services 86
Claire Abson and Alastair Allan

11 Research Methods for Advanced Web Searching 94
Alastair Allan

12 Searching in Unfamiliar Fields 113
Tom Bourner and Sue Greener

13 Sources of Population Statistics 121
Keith Dugmore

14 An Introduction to Bibliometrics 130
Silvia Salini

15 Choosing and Using Software for Statistics 144
Felix Grant

16 Computer Support for Data Analysis 152
Clifford E. Lunneborg

Part III Measurement and Experimentation 157

17 Instrumentation in Experimentation 159
Anand D. Pandyan, Frederike van Wijck and Garth R. Johnson

18 Randomised Trials 171
Douglas G. Altman

19 Laboratory and Industrial Experiments 180
Tony Greenfield

20 Experiments in Biological Sciences 193
Roger Payne

21 Survey Research 202
David de Vaus

22 Theory and Practice of Qualitative Research 214
Irena Ograjensek

23 Kansei Engineering 231
Lluis Marco-Almagro

24 Principles of Sampling 244
Peter Lynn

25 Sampling in Human Studies 255
Peter Lynn

26 Interviewing 264
Mark Hughes

27 Measurement Error 275
Roland Caulcutt

Part IV Data Analysis 287

28 Elementary Statistics 289
David J. Hand

29 Further Statistical Methods 299
David J. Hand

30 Spreadsheets: A Few Tips 307
Tony Greenfield and Andrea Benn

Part V Special Tools 323

31 The Value of Mathematical Models 325
Andrew Metcalfe

32 Deterministic Models 342
Andrew Metcalfe

33 Stochastic Models and Simulation 357
David Green and Andrew Metcalfe

34 Optimisation 372
Aiden Fisher and Andrew Metcalfe

Part VI Presentation 387

35 Writing the Thesis 389
Tony Greenfield

36 The Logic of a Research Report 400
Tom Bourner and Linda Heath

37 Presenting Data 412
Sue Greener

38 Presenting and Sharing Your Research 419
Sue Greener

39 Reporting Research 429
Iveta Simera and Douglas G. Altman

40 Social Media - How to Make ItWork for You as a Post-Graduate 440
Suzanne Fraser-Martin and Catherine Fraser-Martin

Part VII Next Steps 455

41 Protection and Exploitation of Intellectual Property 457
Patrick Andrews

42 Career Opportunities 470
Sara Shinton

Index 479

Textauszug

Preface to the Third Edition

“Would you like to produce a third edition?” asked Heather. “Wiley have bought the rights from Hodder. I read the second edition and looked for competition. There is no other book about research methods as good as yours”.

She assured me that I could apply my own style and that she and others at Wiley would help me as much as they could.

Years have passed since the first edition, and I have grown old, so this is my last work for the scientific and technical literature. I have depended entirely on all authors of chapters, for whose patience and understanding I am immensely grateful. They are all erudite and enthusiastic about their own subjects and eager to inspire you, our students, to do first-class research. I hope my own story will also inspire you.

This is a personal story. Perhaps this is the wrong place for a personal story but I want to tell it, as my attempt to inspire you.

“Is statistics a science?” is a hackneyed old question. It discomforts me. The question is needless. It is needless because it is predicated by the assumption that there are many sciences.

We have split science into several separate sciences, but the splits are artificial.

What is my science? I am a scientist. (No splits.)

We do split science into subject areas for pedagogical convenience in schools and universities. I do remember most of the chemistry, physics and biology I learned at school 70 years ago. I could not claim to be a chemist, physicist or biologist. But I would not say, as I was once shocked to hear a statistician say, “I cannot discuss the design of an aerofoil because I am not an aeronautical engineer; I am a statistician”.

Statistics is a part of science, but it is not ‘a science’; it is a subject area within science just as is chemistry. And it has no discrete boundary, as neither does chemistry.

Statistics provides method to science:

Do you ever notice something; describe it; ask yourself, “What is it? Why is it? Where it it? Is it useful to me or to anybody else? Does it have any relationship to anything else?” Then you have the makings of a scientist.

But, and this is where the usefulness of statistics arrives, do you then invent a working assumption, called a hypothesis, that is consistent with what you have observed? If you do, can you then use the hypothesis to make predictions?

Now, you must see clearly that statistics is an essential tool of science. You can test your predictions by experiments or further observations and modify the hypothesis in the light of your results. The scientific method insists that you keep revising your hypothesis and experimenting until you can detect no discrepancies between your hypothesis and your observations. You may then, correctly in the scientific realm, tell the world that you have a theory that may explain a class of phenomena.

A theory, by my description and by dictionary definition, is a framework within which observations are explained and predictions are made.

I once proposed a curriculum approach to representation of statistics as the cement for binding science's subject areas. This was in a paper, The polymath consultant, at the first meeting of ICOTS (International Conference on Teaching Statistics). The Times newspaper published a short version of it. The UK secretary of state for education, Keith Joseph, was interested enough to invite me to discuss it, and he encouraged me to promote the idea in universities. Nobody else took any notice. Yet I still believe that there was an idea that could be developed as part of our search for the future of data analysis. We must teach that statistical methods are just as part of, and just as applicable, in social studies as they are in physics and chemistry; and that they are as useful in linguistics, history and geography as much as they are in engineering and marketing.

Collections of worked practical cases, such as those by Cox and Snell (1981), must help and we need more of them. A recent book (Greenfield and Metcalfe 2007) aims at this with more than 50 worked cases about school absence, metro noise levels, water fluoridation, diamond prospecting, wine tasting, compulsive gambling, prosthetic heart valves and many more.

Evidence is the life-blood of science and scepticism is its spark of life. Data analysis is the flux of evidence. We should continue to ensure that all scientists, in all subject areas, and these include you, perceive it as such. Always you must be sceptical about any assertion that has no evidential support. Nullius in verba.

Frances Ashcroft, a truly great scientist of this, the twenty-first century, tells us in a recent book how her own research excited her.

I discovered that the KATP channel sits in the membrane that envelops the beta-cell and regulates its electrical activity and thereby insulin release.… The breakthrough came late at night when I was working alone.… I was ecstatic. I was dancing in the air, shot high into the sky on the rocket of excitement with the stars exploding in vivid colours all around me. Even recalling that moment sends excitement fizzing through my veins, and puts a smile on my face.

There is nothing — nothing at all — that compares to the exhilaration of discovery, of being the first person on the planet to see something new and understand what it means. It comes all too rarely to a scientist, perhaps just once in a lifetime, and usually requires years of hard grind to get there. But the delight of discovery is truly magical, a life-transforming event that keeps you at the bench even when times are tough. It makes science an addictive pursuit.

That night I felt like stout Cortez, silent upon his peak in Darien, gazing out across not the Pacific Ocean, but a landscape of the mind. It was crystal clear where my mental journey must take me, what experiments were needed and what the implications were.

Next morning, all certainty swept away, I felt sure my beautiful result was merely a mistake. There was only one way to find out. Repeat the experiment — again and again and again. That is the daily drudgery of a scientific life: it is very far from the ecstasy of discovery.

The Spark of Life Electricity in the Human Body

Frances Ashcroft

Such reporting inspired me to read the rest of the book even though, in her last paragraph, she warns that all of us, including you, cannot expect winning without drudgery. Thomas Edison expressed this well:

Genius is one percent inspiration, ninety-nine percent perspiration.

Spoken statement (c. 1903); published in Harper's Monthly (September 1932)

Many writers in the past have felt the same elation as Frances Ashcroft. John Keats, for example, recorded that feeling:

Then felt I like some watcher of the skies

When a new planet swims into his ken;

Or like stout Cortez when with eagle eyes

He star'd at the Pacific — and all his men

Look'd at each other with a wild surmise —

Silent, upon a peak in Darien.

John Keats

Mary Shelley told us how Doctor Frankenstein's feeling went further from the beauty of scientific achievement to disgust at what he had done.

The different accidents of life are not so changeable as the feelings of human nature. I had worked hard for nearly two years, for the sole purpose of infusing life into an inanimate body. For this I had deprived myself of rest and health. I had desired it with an ardour that far exceeded moderation; but now that I had finished, the beauty of the dream vanished, and breathless horror and disgust filled my heart.

Frankenstein (chapter 5) Mary Wolstencroft Shelley

If, as a scientist, you can keep powering the bellows that inflame your spark of inspiration into a bright light of scientific achievement, scientists will acknowledge that you are one of them. But, first, you must be sure that you believe you are a scientist. You must have started somewhere, sometime. Here is how and when and where I started.

“Tell Father that lunch is ready,” said Mother. “He's in the garage”.

I loved Sunday lunch when I was six, especially when it was roast beef, Yorkshire pudding, dark green cabbage and rich gravy. I went to the garage to summon Father to the table where he would display his knife sharpening and carving skills.

He was on the floor, asleep, and his face had a bluish greenish tinge.

I ran to Mother. She quickly opened the doors and windows and called an ambulance. She dragged him onto the lawn and pumped his chest. He breathed and his face turned grey. An ambulance arrived. The men put a mask over his face. It was connected by a rubber tube to a cylinder of oxygen. His face turned pink. The ambulance drove away and we had lunch, a little late.

Carbon black is an amorphous carbon with a high surface-area-to-volume ratio. It is used as a pigment and reinforcement in rubber and plastic products. It also helps to conduct heat away from the tread and belt area of the tyre, reducing thermal damage and increasing tyre life. It is very expensive. It was even more expensive when I was six and Father thought he could make a lot of money by producing it from cheap by-products, usually discarded, from coal distillation or coke making. One of these was naphtha and, as a chemical engineer, he knew where he...

Produkt-Details

• Erscheint lt. Verlag: 25.8.2016
• Sprache: englisch
• Themenwelt: Mathematik / Informatik ► Mathematik ► Statistik
• Themenwelt: Mathematik / Informatik ► Mathematik ► Wahrscheinlichkeit / Kombinatorik
• Themenwelt: Medizin / Pharmazie ► Medizinische Fachgebiete
• Themenwelt: Naturwissenschaften
• Themenwelt: Technik
• Schlagworte: Angewandte Wahrscheinlichkeitsrechnung u. Statistik • Applied Probability & Statistics • Medical Science • Medical Statistics & Epidemiology • Medizin • Medizinische Statistik u. Epidemiologie • postgraduate research social media, new research tools, new research methods, latest methods postgraduate research, postgraduate research how to, postgraduate research guide, organizing research, Kansei engineering, reporting medical research, research funding how to, research funding guide, funding postgraduate research, research presentation how to, research presentation guide • Research Methodologies • Sociology • Soziologie • Soziologische Forschungsmethoden • Statistics • Statistik
• ISBN-10: 1-118-76299-1 / 1118762991
• ISBN-13: 978-1-118-76299-8 / 9781118762998