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- Herausgeber: John Wiley & Sons
- Kategorie: Wissenschaft und neue Technologien
- Sprache: Englisch
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.
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RESEARCH METHODS FOR POSTGRADUATES
Third Edition
Edited by
Tony Greenfield with Sue Greener
This edition first published 2016 © 2016 John Wiley & Sons, Ltd
First Edition published in 1996 Second Edition published in 2002
Registered officeJohn Wiley & Sons, Ltd, The Atrium, Southern Gate, Chichester, West Sussex, PO19 8SQ, United Kingdom
For details of our global editorial offices, for customer services and for information about how to apply for permission to reuse the copyright material in this book please see our website at www.wiley.com.
The right of the author to be identified as the author of this work has been asserted in accordance with the Copyright, Designs and Patents Act 1988.
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Library of Congress Cataloging-in-Publication Data
Names: Greenfield, Tony, editor. | Greener, Sue, editor.
Title: Research methods for postgraduates / edited by Tony Greenfield with Sue Greener.
Description: Third edition. | Chichester, UK ; Hoboken, NJ : John Wiley & Sons, 2016. | Includes index.
Identifiers: LCCN 2016011607 (print) | LCCN 2016016287 (ebook) | ISBN 9781118341469 (pbk.) | ISBN 9781118763001 (pdf) | ISBN 9781118762998 (epub)
Subjects: LCSH: Research–Methodology.
Classification: LCC Q180.55.M4 R473 2016 (print) | LCC Q180.55.M4 (ebook) | DDC 001.4/2–dc23
LC record available at https://lccn.loc.gov/2016011607
A catalogue record for this book is available from the British Library.
ISBN: 9781118341469
CONTENTS
About the Author
List of Contributors
Preface to the Third Edition
Preface to the Second Edition
Preface to the First Edition
Part I: First Steps
1: A View of Research
Introduction
Contents
Creativity
2: The Research Journey: Four Steps to Success
Part 1: Reviewing the Field
Part 2: Theory Building
Part 3: Theory Testing
Part 4: Reflection and Integration
Summary and conclusions
References
Notes
3: Managing Your Doctorate
Introduction
Approaching and Starting Your Doctorate
Planning Your Research Project
Organising Your Research
Managing Your Research
Managing Your Relationship with Your Supervisory Team
Managing Yourself
Completing Your Submission
Preparing for Your Viva
On the Day
Disseminating Your Findings
Conclusions
References
Note
4: Documenting Your Work
Why Document?
Documenting Data
How to Document?
In Conclusion
References
5: Ethics of Research
Introduction
Background
Codes of Conduct
Politics
Cutting Corners
Fraud
References
6: Plagiarism
Some Examples
Stopping Plagiarism
Conclusion
7: Critically Reviewing Your Own Research
Introduction
A Checklist from the Experts in Reviewing Research
The Issue of Criticality
Conclusions
Appendix
Note
Part II: Support
8: Research Proposals for Funding
Introduction
Find a Suitable Funder
Plan Your Proposal
Write Your Proposal
How Much to Charge?
Checks before Submission
What Happens Next?
If You Are Unsuccessful
If You Are Successful
The Future
9: Who Can Help?
Introduction
Supervisors
Attracting Ideas
Academic Sources of Help
Other Sources of Help
Summary
10: Information and Library Services
Introduction
Know Your Librarian
Develop the Skills You Need
Tracking down Books
Journal Articles and Electronic Sources
Accessing Other Libraries
Studying at a Distance
Keep a Record of What You Have Done
Research Data Management
Conclusion
References
11: Research Methods for Advanced Web Searching
Some Background
How It Works and How to Work It
Web Filtering
Finding the Academic Websites That Search Engines Cannot Find
Finding Journal Articles
Conclusions
List of Websites Referred to in the Text
References
12: Searching in Unfamiliar Fields
A Strategy for Search
Searching in Unfamiliar Territory
Keywords
Conclusions
Appendix: Specimen Search Profile
References
13: Sources of Population Statistics
Why Are Statistics about Populations So Important?
Populations and Classifications
Which Population Counts Would You Ideally Like for Your Project?
Which Organisations Produce and Supply Data?
What Are the Major Sources of Population Statistics?
Conclusions: Hunting Population Statistics
14: An Introduction to Bibliometrics
Why a Chapter on Bibliometrics?
Introduction
The Definition of Bibliometrics
The History of Bibliometrics
Bibliometrics as a Research Field
Bibliometrics and Evaluation of Research
Bibliometrics Indicators
Conclusions
References
Notes
15: Choosing and Using Software for Statistics
What Can You Afford?
What Sort of Person Are You?
Emphasising the Graphical
Taking Direct Command of Your Software
Going for the Best of Both Worlds
Special Cases
Suitability for Your Purpose
And Finally …
16: Computer Support for Data Analysis
Introduction
Five Stages of Statistical Method
Confirmatory and Exploratory Analysis
Computing Resources
Standard Statistical Packages
Specialised Statistical Packages
Conclusion
References
Part III: Measurement and Experimentation
17: Instrumentation in Experimentation
Introduction
Concept of Measurement
Measurement Systems: Basic Principles
Performance of Measurement Systems
Evaluation of Measurement Instrumentation
Discussion
Websites for Software and Hardware
Websites on Safety and Standards
References
18: Randomised Trials
Introduction
Trial Design
Analysis
Interpretation of Results
References
19: Laboratory and Industrial Experiments
Introduction
Principles of Experimental Design
References
20: Experiments in Biological Sciences
Blocking
Treatment Structure
Other Types of Blocking Structure
Assumptions of the Analysis
Transformations
Generalised Linear Models
Spatial Covariance Models
Repeated Measurements
Conclusion
References
21: Survey Research
What Is a Survey?
Dimensions of Surveys
Questionnaire Design
Modes of Questionnaire Administration
Ethics
Practicalities
Pros and Cons of Each Method of Administration
References
Further Reading
22: Theory and Practice of Qualitative Research
What Is Qualitative Research, and Why Use It?
Qualitative versus Quantitative Research
Typologies of Qualitative Research
Questioning-Driven Qualitative Research Methods
Observation-Driven Qualitative Research Methods
Software Support of Qualitative Research
Reliability and Validity of Qualitative Research
References
23: Kansei Engineering
An Introduction to Kansei Engineering
A Model for Kansei Engineering Studies
An Example Using Printed Paper Sheets
References
24: Principles of Sampling
Introduction
Why Sample?
Sample Design
Inference
Bias, Variance and Accuracy
Non-probability Sampling
Probability Sampling
Capture–Recapture Sampling
Adaptive Sampling
Sample Size
Weighting
Summary
References
25: Sampling in Human Studies
Introduction
Important Considerations
Stratification
Sampling Frames
Sampling General Populations
Sampling Special Populations
Screening a General Population Sample
Weighting
References
26: Interviewing
Introduction
The Case for and against Interviewing
Varieties of Interview
Internet Interviewing
Interview Questions
Interviewing as a Process
Upon Arrival
Recording Interviews
Analysing Interviews
Final Reflections upon Interviewing
Internet Resources
References
27: Measurement Error
Introduction
Scales of Measurement
Four Researchers Who Need to Measure
How Good Are Their Measurements?
How Can We Best Describe the Performance of a Process?
Assessing a Measurement Process in Psychology
Assessing a Measurement Process in Engineering Research
A Procedure for Assessing Engineering Measurement Processes
A Procedure for Assessing Chemical Measurement Processes
Errors in Data Taken from Computer Files
Measurement Uncertainty
Summary
References
Part IV: Data Analysis
28: Elementary Statistics
Introduction
Scales
Basic Measures
Simple Distributions
Estimating Parameters
Testing Hypotheses
Conclusion
References
Further Reading
29: Further Statistical Methods
Introduction
Regression Analysis
Logistic Regression
Discriminant Analysis
Analysis of Variance
Other Methods
Time Series
Other Techniques
References
Further Reading
30: Spreadsheets: A Few Tips
Introduction
Part One: Data Source
Part Two: Data Analysis
Reference
Part V: Special Tools
31: The Value of Mathematical Models
Introduction
Mathematical Modelling
Learning Mathematics
Mathematical Software
Literature Searches
Reading Papers with Mathematical Content
Promoting Applications of Mathematics
Advanced Courses
Types of Mathematical Models
Typing Mathematics in Your Thesis
Summary
References
32: Deterministic Models
Introduction
Mathematical Software
Discrete and Continuous Variables
Linear and Non-linear Systems
Vibration Control
Vibration Control of an Out-of-Balance Rotor
Finite Element Modelling
Finite Difference Method
Control Theory
Catastrophe Theory (Singularity Theory)
Wave Motion
Conclusion
References
33: Stochastic Models and Simulation
Introduction
Random or Deterministic?
Random Number Generation
Comparing Random and Deterministic Models for Arrivals
Synchronous or Asynchronous Simulation
Classifying Stochastic Models
Applications of Markov Chains
Applications of Point Processes and Simulation
Applications of Time Series, Signal Processing and Simulation
A Random Field Model for Rainfall
Other Random Field Models
How Can Maths Fight Influenza?
Bayesian Modelling
Conclusion
References
34: Optimisation
Introduction
Calculus
Descent Algorithms
Linear Programming
Mathematical Programming
Duality
Dynamic Programming and Stochastic Dynamic Programming
Simulated Annealing and Genetic Algorithms
Conditional Value at Risk
Multi-objective Optimisation
Case Study (Sanchez
et al.
, 2012)
References
Notes
Part VI: Presentation
35: Writing the Thesis
Introduction
Structure
Style
Statistics
References
Further Reading
36: The Logic of a Research Report
Introduction
Background
The Argument
Discussion
Summary and Conclusions
References
Notes
37: Presenting Data
Introduction
Key Points Visualisation
Presenting Visualisations to Lay Audiences
Using Visualisations in the Process of Research
A Final Word on Good Practice
38: Presenting and Sharing Your Research
Introduction
What Kind of Event?
The Keys to Great Personal Presentations
Sharing Your Presentation
39: Reporting Research
Ethical Imperative of Responsible Publication of Research Studies
General Principles of Reporting Medical Research
Reporting Guidelines
Reporting Randomised Controlled Trials: The Consolidated Standards of Reporting Trials (CONSORT) Statement
Reporting Analytical Observational Studies: The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement
Reporting Systematic Reviews: The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) Statement
The Enhancing the Quality and Transparency of Health Research (EQUATOR) Library for Health Research Reporting: A Free Online Resource
Concluding Remarks
References
Further Reading
Note
40: Social Media – How to Make It Work for You as a Post-Graduate
Hitting the Toenail on the Head: A Small Portion of Spam
Websites
Social Networking Sites
Blogs and Micro-blogs
A Word about Trolls
Spell Checkers
Backups
Clouds
Part VII: Next Steps
41: Protection and Exploitation of Intellectual Property
Introduction
What Is Intellectual Property?
Know-how
Copyright
*
Design Right and Registered Design
*
Unregistered or ‘Intellectual’ Assets
Trademarks
*
Patents
*
How to Turn Your IP into Money
Make an Outline Business Plan
Patents – Pros and Cons
Conclusion
42: Career Opportunities
Choosing the Right Career
Common Destinations of Doctoral Graduates
Key Messages
Acknowledgements
References
Index
EULA
List of Tables
Chapter 7
Table 7.1
Table 7.2
Chapter 12
Table 12.1
Table 12.2
Chapter 13
Table 13.1
Table 13.2
Table 13.3
Table 13.4
Chapter 14
Table 14.1
Chapter 17
Table 17.1
Table 17.2
Table 17.3
Chapter 18
Table 18.1
Chapter 19
Table 19.1
Table 19.2
Chapter 20
Table 20.1
Table 20.2
Table 20.3
Table 20.4
Chapter 21
Table 21.1
Table 21.2
Table 21.3
Table 21.4
Table 21.5
Table 21.6
Table 21.7
Table 21.8
Table 21.9
Chapter 22
Table 22.1
Table 22.2
Table 22.3
Table 22.4
Chapter 23
Table 23.1
Table 23.2
Chapter 26
Table 26.1
Table 26.2
Chapter 27
Table 27.1
Table 27.2
Chapter 28
Table 28.1
Chapter 29
Table 29.1
Chapter 39
Table 39.1
List of Illustrations
Chapter 11
Figure 11.1
Google Advanced Search. http://www.google.co.uk/advanced_search?hl=en.
Figure 11.2
Google Advanced Search: filtering results. http://www.google.co.uk/advanced_search?hl=en.
Figure 11.3
Google Scholar Advanced Search page. http://scholar.google.co.uk/advanced_scholar_search?hl=en&as_sdt=1,5.
Chapter 14
Figure 14.1
JASA 2010 – percent distribution of citations. Data from Web of Science 2012.
Chapter 17
Figure 17.1
Simple diagram of a generic measurement system.
Figure 17.2
An example of a recording of human muscle activity. The signal was recorded using bipolar electrodes (a method of improving the signal-to-noise ratio) with a sampling frequency of 1980. There was evidence of data saturation (amplification of the signal was too high) as identified in the boxed section. If the EMG was quantified (using a root mean square procedure) prior to filtering of the means frequency noise, the mean was calculated as 0.299 μV; after the removal of the means frequency using an eighth-order Butterworth notch filter, the mean reduces to 0.295 μV.
Figure 17.3
(a) The measurement of human sway in 2D when measured at 1000 Hz and the estimated path length is 1483 mm. (b) The same measurement of human sway in 2D when down-sampled to 100 Hz and the estimated path length is 154.46 mm.
Chapter 19
Figure 19.1
Graph showing tensile strength (response variable) against stirring speed (control variable).
Figure 19.2
Graph showing a two-factor design.
Figure 19.3
The three-factor situation.
Figure 19.4
Catheter fixed to a valve body.
Chapter 22
Figure 22.1
Typical elements of an online focus group – the respondent view.
Figure 22.2
Typical elements of an online focus group – the client view.
Figure 22.3
A sample collage.
Chapter 23
Figure 23.1
A model for developing kansei engineering studies.
Figure 23.2
Affinity diagrams are often used for spanning the semantic space in kansei engineering studies.
Figure 23.3
An example of scales used in KE studies.
Figure 23.4
Radar plot for kansei words
elegant
,
formal
and
serious
.
Figure 23.5
The semantic space in the typography example.
Chapter 24
Figure 24.1
Three different sampling distributions produced by three different sample designs A, B and C, where μ is the population parameter.
Chapter 27
Figure 27.1
Thirty people take a test twice.
Figure 27.2
Only one person gets the same score on both occasions.
Figure 27.3
Measurements by four operators.
Figure 27.4
A normal distribution: mean, 20.1, standard deviation, 0.17.
Figure 27.5
Measurement error creates uncertainty.
Chapter 28
Figure 28.1
Histogram of 799 interpulse waiting times.
Chapter 30
Figure 30.1
The first few rows of a spreadsheet with short labels for columns and unique case numbers for rows.
Figure 30.2
The general area for formatting cells: making the selection.
Figure 30.3
The dialogue box for formatting entries of cholesterol values.
Figure 30.4
Selecting the headings to freeze panes.
Figure 30.5
A list is generated.
Figure 30.6
Pick from list: (a) the drop-down list; (b) alphabetical list.
Figure 30.7
Quick Access Toolbar.
Figure 30.8
The data form.
Figure 30.9
Data > Data Validation.
Figure 30.10
The validation dialogue: (a) for a decimal number; (b) for a date.
Figure 30.11
Data > Filter.
Figure 30.12
Customising the search.
Figure 30.13
The autofilter procedure.
Figure 30.14
Using Excel's own functions.
Figure 30.15
PivotTable > PivotTable or PivotChart, automatic chart procedures.
Figure 30.16
Data Analysis tools.
Figure 30.17
(a) Manage Excel Add-Ins; (b) select Analysis ToolPak.
Figure 30.18
Data Analysis ToolPak now added to Excel.
Figure 30.19
The Function dialogue box for Histogram.
Figure 30.20
Using the Help option, via Data Analysis ToolPak.
Figure 30.21
Statistical tools for Apple Mac Users.
Chapter 31
Figure 31.1
Maths is Cool. The other 12 posters can be seen at: http://www.newton.ac.uk/wmy2kposters/. Reproduced with permission of Isaac Newton Institute: graphic design and text, A Burbanks and HK Moffat; iceberg images, British Antarctic Survey.
Chapter 32
Figure 32.1
Modelling particles in fluid flows. Courtesy of Sarthok Sircar and Tony Roberts.
Figure 32.2
Model of rotor. Metcalfe and Burdess, 1992. Reproduced with permission from Springer.
Figure 32.3
Mode shapes. Qef (public domain), via Wikimedia Commons. https://upload.wikimedia.org/wikipedia/commons/c/c5/Harmonic_partials_on_strings.svg
Figure 32.4
Control of a rotating shaft. Metcalfe and Burdess, 1992. Reproduced with permission from Springer.
Figure 32.5
Vibration on a railway track. Courtesy of Roger Hosking.
Figure 32.6
Wall shear stress in umbilical cord. Reproduced with permission of David Wilkie.
Figure 32.7
Simulation of non-inertial fluid mixing in a cubic cavity (Jewell, 2009; see also Jewell, 2012).
Figure 32.8
Comparison of experimental and modelled flows of water over ice. Skene
et al.
(2015).
Chapter 33
Figure 33.1
Two different ordered sequences of the same set of numbers.
Figure 33.2
Schematic of single-server queue. A customer arriving to find the server free will immediately go into service; otherwise, they will join a waiting line and be served in order of arrival. Queueing theory says that if there is no correlation between these times, then the averaged occupancy of the system will be 0.5 customers. However, we can simulate this system in three ways to show the effects of serial correlation.
Figure 33.3
Effect of serial correlation of arrival times on average system occupancy. The vertical axis gives the averaged occupancy, whereas the horizontal axis gives the actual arrival times of the customers. To generate these times, we use random numbers
U
i
(uniformly distributed random numbers between 0 and 1, denoted
U
[0, 1)). In the blue trace, we have used the numbers
U
i
for the inter-arrival times and the numbers 1 −
U
i
for service times of customer
i
. In the green trace, we have used separate number streams
U
i
and
U
j
for customer i times
m
, and in the red trace we have used the numbers
U
i
for both the inter-arrival times and service times of customer
i
. This is an extreme case to show the effects. Sometimes when simulating systems it is actually beneficial to employ correlation, and hence the possible existence and effects of correlation are something that a practitioner must be aware of in designing simulation models.
Figure 33.4
RANDU – a not so random PRNG.
Figure 33.5
A telephone tower in Stockholm, Sweden, with 5000 connected lines. It was used between 1887 and 1913, but the tower stood there until 1953, when it fell down after a fire. www.flickr.com/photos/tekniskamuseet/6838150900/in/set-72157629589461917
Figure 33.6
‘Telephone exchange Montreal QE3 33’ by various photographers for Cassell & Co. –
The Queen's Empire
. Volume 3. Cassell & Co. London. (Licensed under Public Domain via Commons, https://commons.wikimedia.org/wiki/File:Telephone_exchange_Montreal_QE3_33.jpg -/media/File:Telephone_exchange_Montreal_QE3_33.jpg)
Figure 33.7
Artist's depiction (1890) of Broadway and John Streets in Manhattan before and after (circa 1910) the undergrounding of telephone wires around the time of the introduction of telephone exchanges. (Casson 1910).
Figure 33.8
MTB rainfall field model. Courtesy of Dale Mellor.
Chapter 34
Figure 34.1
An example of a simplex algorithm for minimising a function of two variables α and β. The initial function evaluations are made at the points shown by crosses. As 37 is the greatest value, this point is reflected in the line joining the other two points to arrive at the square. The function evaluation at the square is 18, so the point with function evaluation 24 is reflected to the point shown by the circle, and the function evaluation at the triangle is 16. The cross with function evaluation 21 is reflected to the dot and so on.
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About the Author
Tony Greenfield was born in Chapeltown, South Yorkshire on 26 April 1931 to Geoffrey James Greenfield (1900–1978) and Hilda Aynsley (1903–1976).
Tony worked in a Cumbrian iron mine when he left Bedford School at the age of 17. He later worked in coal mines, a brass tube factory and a copper mine and studied mining engineering at Imperial College London. He received the diploma in journalism from the Regent Street Polytechnic, worked technical journals and on the Sunday Express and Sunday Mirror before turning to technical journalism, in Sheffield, for 10 years. He was an active member of the Sheffield Junior Chamber of Commerce of which he was chairman of the Local Affairs, Business Affairs and Public Speaking committees and editor of The Hub, the chamber's monthly magazine. At the 1963 conference in Tel Aviv of Junior Chamber International, he was acknowledged as the editor of the best junior chamber magazine in the world.
He moved into the steel industry to write technical reports for Operations Research (OR) scientists. There he found satisfaction in solving production problems, and studied OR, mathematics, statistics and computing, leading to an external degree from University College London. He moved into steel research and became head of process computing and statistics. Much of his work was in design and analysis of experiments for which he received his PhD. He co-authored the first interactive statistics package to be written in Fortran. When the laboratories closed, he joined the medical faculty of University of Sheffield where he was statistician to a multi-centre study of cot death. He taught medical statistics to undergraduates, supported post-graduates and medical staff with consultancy. Tony moved to Belfast as professor of medical computing and statistics at Queen's University. Early retirement enabled him to work as a research consultant.
Tony's passion is to persuade all scientists and engineers to write, speak and present their work in language that other people understand well enough to use. And, like W.B. Yeats, he asks scientists to “think like a wise man but communicate in the language of the people”.
Like Isaac Asimov, he is “on fire to explain and doesn't indulge in scholarly depth”. He believes strongly that the economic fortune of Europe depends on the success in the world markets of our manufacturing industries.
“Statisticians and statistical practitioners across Europe know that statistical methods have improved business and industrial peformance – and can do so in the future”, he says. “Our national quality of life will be improved and secured if we can communicate the philosophy, as well as the methods, of statistics to engineers and others in the manufacturing and the service industries. Businessmen and engineers need to understand the benefits of applied probability and statistics; they need to understand how the methods are applied to their own work; they need to be fully converted to a frame of mind that will make them automatically question sources of variability in everything that they do and, without outside prompting, adopt the statistical approach”.
He and others founded ENBIS to stimulate the application of statistical methods to economic and technical development and to business and industry across the whole of Europe. They have created a networking forum for the exchange of ideas between statistical practitioners. He has spread this passion by speaking in many cities across Europe from Tel Aviv, through Turin, Budapest, Ljubljana, Copenhagen, Brussels, Sheffield, Newcastle and London.
List of Contributors
Claire Abson
Sheffield Hallam University, Sheffield, UK
Alastair Allan
University of Sheffield, Sheffield, UK
Douglas G. Altman
University of Oxford, Oxford, UK
Patrick Andrews
Hawkshaw Product Design Ltd, Crieff, Scotland, UK
Andrea Benn
University of Brighton, Brighton, UK
Tom Bourner
Professor Emeritus, Brighton Business School, University of Brighton, UK
Roland Caulcutt
Caulcutt Associates, Salisbury, UK
Shirley Coleman
ISRU, School of Maths and Stats, Newcastle University, UK
David de Vaus
Emeritus Professor, FASSA, Institute for Social Science Research, University of Queensland, Brisbane, Australia
Keith Dugmore
Demographic Decisions Ltd, London, UK
Aiden Fisher
University of Adelaide, SA, Australia
Catherine Fraser-Martin
Independent researcher, UK
Suzanne Fraser-Martin
Independent researcher, UK
Felix Grant
Lecturer and consultant, UK
David Green
School of Mathematical Sciences, University of Adelaide, SA, Australia
Sue Greener
Brighton Business School, University of Brighton, UK
Tony Greenfield
Greenfield Research, UK (retired)
David J. Hand
Imperial College, London, UK
Linda Heath
Brighton Business School, University of Brighton, UK
Mark Hughes
Brighton Business School, University of Brighton, UK
Garth R. Johnson
Newcastle University, Newcastle, UK
Clifford E. Lunneborg
R Foundation, Boston, MA, USA
Peter Lynn
Institute for Social and Economic Research, University of Essex, Colchester, UK
Lluis Marco-Almagro
Universitat Politecnica de Catalunya, BarcelonaTech, Barcelona, Spain
Vivien Martin
Brighton Business School, University of Brighton, UK
Lowry McComb
Durham University, UK
Andrew Metcalfe
School of Mathematical Sciences, University of Adelaide, SA, Australia
Juliet Millican
CUPP, University of Brighton, UK
Irena Ograjenšek
Faculty of Economics, University of Ljubljana, Slovenia
Anand D. Pandyan
Keele University, Newcastle under Lyme, UK
Roger Payne
VSN International & Department of Computational and Systems Biology, Rothamsted Research, Harpenden, UK
Silvia Salini
University of Milan, Italy
Sara Shinton
Shinton Consulting Ltd, Galashiels, UK
Iveta Simera
Centre for Statistics in Medicine, Nuffield Department of Orthopaedics, Rheumatology and Musculoskeletal Sciences University of Oxford
Stan Taylor
School of Education, Durham University, Durham, UK
Frederike van Wijck
Glasgow Caledonian University, Glasgow, Scotland, UK
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 could get as much as he wanted very cheap. In those days, the Americans made most of the world's carbon black from natural gas and it cost about £5000 a ton (imperial spelling): a lot, especially if you convert that into today's money. Nowadays, with many more sources of materials and more efficient production, it is worth about £500 a tonne (note the SI spelling).
Father explained as much of this to me as I could understand and he showed me his experimental machine. So far as I can remember, nearly 60 years later, it comprised a rotating drum with cooling water circulating through it. There was a row of tiny jets through which he pumped naphtha that burned, with only partial combustion, so that carbon black deposited on the cold drum surface. Naphtha is a crude mix of oils that drained out of the bottoms of coke ovens where it was used by burning to heat the ovens.
I learned, when I was six, that Father was a scientist, an engineer and an experimentalist. But his research had its perils, including the possibility of carbon monoxide poisoning.
Father explained many things to me over the years.
He drove to a coke oven plant in Scunthorpe when I was 11. I went too but, in case I was bored, I carried a Just William book (by Richmal Compton). At the ovens, we sat all night measuring things as they happened. Father told me, “This is called ‘dynamic measuring’ ”. I watched, fascinated, as ink flowed onto rotating graphs. In the morning, Father analysed the data and advised the works manager on how to improve his benzole production. Benzole (a mix of benzene and toluene) had been seen, by coke-makers, as a waste by-product. In 1942, it was an essential fuel for the Spitfire.
This was science in the raw and I was excited, never bored.
I was 15 when I bought an ancient motorbike that wouldn't go. Father commented that I would be a competent mechanic and understand internal combustion engines by the time I was allowed to drive it. A year later I had fixed it but petrol was rationed. I decided to make my own. I had fitted the bike with acetylene lights instead of electric lights. A local garage gave me a drum of (calcium) carbide that they no longer needed. Water drips onto carbide to produce acetylene which, at one time, was used for lighting. I also knew that acetylene (C2H2) could be polymerised to benzene (C6H6) by contact with red-hot iron or most alloys in which iron is the dominant component, at about 700 oC. I wound an electric fire element round the gap between two silicon tubes which I sealed into a large silicon jar connected by a rubber tube to an acetylene generator more than a metre from the jar. I intended to send acetylene into the jar; heat from the fire element would draw the gas up and then down again until benzene appeared. When, eventually, I had made a litre of benzene, I would experiment with mixed proportions of paraffin (not rationed) to discover the best mix to drive my motorbike.
Grandpa's brick garage was integral to the house. Father's was wooden and that is where I had my benzene plant. The power switch was by the door. I started the acetylene generator and let it run for about 10 minutes to expunge all air from the jar. Then I switched on the power; and watched.
Two minutes later, I saw: drip…drip…drip…from the silicon tubes.
Frances Ashcroft expressed my feelings later: “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.”
I watched, enslaved by the sight of my success, but for only a few seconds.
A crack of thunder, a great white light, and the apparatus went through the roof and fell in the garden.
I studied the hole in the roof and caught the next bus to Worthing. I arrived home late at night. Father was still up. I said nothing. “Are you afraid of me?” he asked. “Yes”. “No need”, he said. “I am proud of you”.
Weeks later, my physics master said Father had told him the story and he, too, was proud of me. “You will be a good experimentalist”, he predicted, “but you will always be the servant of others unless you learn about patents”.
When that teacher demonstrated the Michelson–Morley experiment, and said it proved that ether did not exist, I said perhaps it did but it may have properties that were hidden from the experiment. “You have a curious mind, Greenfield”, he said. Father said I had a hypothesis as good as any, and he encouraged me to design an experiment to test it.
Red shift is generally accepted as evidence of universal expansion. Father again encouraged me to design an experiment to test an alternative hypothesis. Although we borrowed a quarry to set up an experiment, the apparatus we designed and built was not good enough.
At 18, I had my first provisional patent for a photographic colour method using the five oxides of vanadium. Kodak were interested but couldn't improve on my colours, the worst of which gave brown instead of green.
Thirty years later:
“I like your style”, said the visiting professor.
His compliment came towards the end of the first course I gave on research methods to the medical faculty of Queen's University, Belfast.
The course arose from my experiences in steel research, in Sheffield University and in Queen's University. In all of these I had found a shocking inability among scientific researchers to write and to speak clearly about their research. Scientific books and papers are so mysterious, so arcane, so bewildering, that scientists can understand only those of their own speciality. They are obscure to others.
I had also been shocked in all these places by the lack of appreciation of statistical and other research methods. A short, sharp course was needed. The faculty dean agreed and encouraged me to run such a course, which I did every year for five years. Students ranged from new medical graduates to senior consultants and professors. Teachers included the dean, a librarian, computer staff, statisticians, professors of clinical psychology, epidemiology and chemical pathology, and the chairman of the research ethics committee.
“I didn't know I had a style”, I replied. “What is it?”
“You always look as if you don't know what you will say next”, the visiting professor told me.
I knew that was true. I always watch students' faces and look into their eyes to be sure that they understand what I am saying. That is an essence of teaching, but it is hard in a lecture hall with 150 students; it is easy in a classroom with no more than 30, which I had.
I can't see the eyes of students when they read a text book, but I can try to write in a style that will grab and keep their attention. Contributors to earlier editions of this book agreed. Unfortunately, the publisher's editors disagreed and, in my view, ruined the style of the second edition. They made changes to the text that were far beyond acceptable editing. They were changes with which I did not agree: changes that affected my style and the styles of other authors. They refused to repair the damage, and eventually I surrendered.
Felix Grant, author of one chapter, wrote to me: “Watching the progress of this whole spectacle has been an education. I shall never look at Hodder or their imprints in the same way again, not only as a writer but as a professional and as an educational book buyer. I admire your tenacity and integrity; I hope I have the same level of commitment to what matters, if it should come to that. I am, after a break of two decades, currently starting on the long process of steering a book of my own through ‘another publisher’. If your experience with Hodder turns out to be typical of changes in publishing's attitudes to quality and verity over that time, I shall be very disappointed”.
I apologise to Felix for my surrender, and to other authors and readers who feel the same. Felix wrote again for this edition. I wish he could see it. Sadly, he died a few months before we went to press.
Wiley have promised no such desecration. They like and enjoy the style that I have encouraged all authors to adopt. Their editors (Debbie Cox and Heather Kay) agree with John Gribbin who wrote, in his New Scientist review of the first edition, “The most useful book any new postgraduate could ever buy”.
Debbie, Heather and Richard Davies have supported this project wonderfully. For myself, and for all the authors and readers, I thank them.
But some authors know that during the course of this work I have developed Parkinson's disease. This delayed production for four years. Heather recruited two angels to help. One is Sue Greener (see chapters 2, 12, 15, 16, 37, and 38) a delightful and positive writer and editor. The other is Liz, my wife, who eagerly follows Heather's instructions to keep me going and keeps in touch with Sue.
Now we have the best edition with revised chapters, new chapters and new writers. You will enjoy reading this book so much that you won't want to put it down. You will start with a journey through the general research scene.… This is where the hard work begins: collect data, analyse and interpret data, and write and publish articles, news items, technical reports and a thesis that you must present to your examiners.
You, the researcher, the problem solver, are responsible to a manager: in a company, a university or a government department. You must report results so that the manager can understand them enough to make decisions. Research does not end with design and analysis. You must interpret and communicate the results. Unless you can describe and explain your results to people who do not share your analytic skills, your results will be worthless. Read the book.
I have no data yet. It is a capital mistake to theorise before one has data. Insensibly one begins to twist fact to suit theories, instead of theories to suit facts.
Sherlock Holmes
A Scandal in Bohemia
Tony Greenfield
Preface to the Second Edition
‘This just might be the most useful book any new post-graduate contemplating research could ever buy’, wrote John Gribbin in his New Scientist review of the first edition of Research Methods. Agreement with that view came from post-graduate researchers. Supervisors and teachers welcomed the book as a prop, even the main course book, for post-graduate courses in research methods.
Comments and advice flowed in and technology advanced. The time arrived for a second edition. Liz Gooster replaced Nicki Dennis as the publisher's commissioning editor and we worked well together. Fortunately, most of the original contributors were willing to revise their chapters but we needed authors for new chapters and some for a few replacements. The Internet and the World Wide Web are here and they have had a profound influence on the ways of post-graduates. This needed to be reflected in many chapters: library, literature reviews, search for funds, information technology and computers, sources of population statistics. References to further reading via the WWW can be offered for almost every chapter.
Reviewers' comments on the first edition were almost all favourable. Here are a few:
Good coverage of major topics relevant to our students (PG training course).
Useful reference material for students with their dissertations and analysing results (MSc Oncology).
Good introduction to many of the skills required by research students.
I have used it a great deal myself. I needed to know about surveys and sampling.
Most useful section is on presentation, particularly
Writing the thesis
.
Aims and approach are sound, even if broad and ambitious. Text well written, concise and convincing. Well-structured. Argument easy to read and digest. Every reader should learn something. New PG students will learn a great deal.
Great strength is the scope and interdisciplinary appeal.
No comparable book.
Some chapters, I was told, may be of interest to some students but had little relevance to others. Well I believe that there is something in every chapter for almost all research students so I asked the authors to refer to many more illustrations of the diverse relevance of their advice. You will find the response in, for example, chapter 28 Instrumentation for research, and in chapter 33 The value of mathematical models.
Some comments could not be reconciled. For example:
Students from engineering valued this book.
Not specific enough for engineers.
Suggestions included:
More emphasis on the Internet.
Some exciting new developments in using the Internet for teaching and research are coming from chemistry departments around the world. Students can send their experimental data across the world and receive it back from computer, spectroscopic or other forms of processing. Similar services for other subjects.
Have a chapter on WAP (Wireless Application Protocol) technology, knowledge based searches and alerts over the Internet and digital television and other multi-media systems.
Chapter needed on navigating the WWW.
Reflect diversity of software packages.
More on creativity.
There is certainly much more emphasis on the Internet and on the WWW. The diversity of software packages, particularly for statistical analysis, is discussed. We have four chapters on creativity. I tried very hard to recruit an author to describe what is happening in chemistry, looking in university departments and in industry, but I failed. ‘He didn't ask me,’ some reader will say. Well please, dear reader, write to me soon, so that we can start to plan the third edition. Nor could I find an author to tell us about WAP. For these, and other topics, I need suggestions and volunteers.
I should also like your comments about how the book is used. I believe it is a good reference text for any post-graduate student. I also believe it is a good framework for any postgraduate research course. Do you agree?
A further suggestion was to construct a FAQ page on the publisher's website. I know this is being considered. Perhaps, by the time this new edition reaches your desk, the page will be there, ready for you to use.
Finally, thanks again to all contributors: those from the first edition for their continuing support; the new recruits for this edition for putting their faith and effort into such a valuable publication. And thanks to Liz Gooster for encouraging and helping me in my role as editor of ‘the most useful book any new post-graduate contemplating research could ever buy’.
Tony Greenfield
Preface to the First Edition
The government proposed in 1994 in their White Paper Realising our Potential that all graduates who wish to study for doctorates should first take a one-year master's course in research methods. Several universities have since introduced such courses and more are planned. This book is a response to that development. It is not intended to be a deeply detailed textbook, rather a set of notes for guidance, to nudge the student's mind into useful avenues, to tell him or her what help is available and to show how he or she can help themselves. This guidance includes many references for further study. As a set of notes it should be useful to all researchers, those studying for doctorates as well as for masters' degrees, for their lecturers too and, indeed, for anybody in any field of research even if a higher qualification is not expected.
The breadth of the subject rules out a single author: none but the most arrogant would pretend to such ability. The publishers and I therefore decided that we should seek contributions from many authors. This posed difficulties of recruitment, of meeting deadlines, of agreeing a common philosophy and adhering to it, and of imposing an editorial style without causing offence to the authors. These difficulties were resolved because there was one clear bond between all the authors: an enthusiasm to help young people to plan, manage, analyse and report their research better than they may otherwise. All of them are busy and successful as researchers and as teachers. I believe that all readers of this book will appreciate how much time and effort, as well as knowledge and experience, the contributors have devoted to its production.
Unusually, this preface is titled Preface to the first edition. This is because I have no doubt that there will be subsequent editions. The situation will change with the introduction of more courses on research methods and experience will accumulate. I invite all readers to tell me how it can be improved: what should be added, what should be omitted, and what should be rewritten. But if you like any of it, please write and tell me. I shall forward your comments on to the authors. They deserve your praise.
Tony Greenfield
Part IFirst Steps
1A View of Research
Tony Greenfield
Introduction
Research, depending on your viewpoint, is:
a quest for knowledge and understanding;
an interesting, and perhaps useful, experience;
a course for qualification;
a career;
a style of life;
an essential process for commercial success;
a way to improve human quality of life;
an ego boost for you; and/or
a justification for funds for your department and its continued existence.
To me, research is an art aided by skills of inquiry, experimental design, data collection, measurement and analysis, by interpretation, and by presentation. A further skill, which can be acquired and developed, is creativity or invention.
This book is mainly about the former set of skills, inquiry to presentation. Further useful topics are described, such as: how to find funds, how to protect your intellectual property and how to share and use the results when your research is concluded.
