The Craft of Research by 
The Essential Guide to Doing Your Research Project by
The Essential Guide to Doing Your Research Project 2e is the ultimate companion to successfully completing your research project. Warm and pragmatic, it gives you the skills and the confidence needed to succeed no matter what happens along the way. The book guides you through every step of your research project, from getting started to analysing data and writing up. Each stage is clearly set out, highlighting best practice and providing practical tips and down-to-earth advice for actually doing research. Key features include: Fully developed companion website including podcasts, worksheets, examples of real projects and links to journal articles Chapter summaries Boxed definitions of key terms Full glossary Suggestions for further readingnbsp;nbsp; Bursting with real world examples and multidisciplinary case studies, this book addresses the key questions posed by anyone hoping to complete a research project. It is the must-have textbook every student needs.
Research in Medical and Biological Sciences: From Planning and Preparation to Grant Application and Publication by
Research in Medical and Biological Sciences covers the wide range of topics that a researcher must be familiar with in order to become a successful biomedical scientist. Perfect for aspiring as well as practicing professionals in the medical and biological sciences, this publication discusses a broad range of topics that are common yet not traditionally considered part of formal curricula, including philosophy of science, ethics, statistics, and grant applications. The information presented in this book also facilitates communication across conventional disciplinary boundaries, in line with the increasingly multidisciplinary nature of modern research projects. Covers the breadth of topics that a researcher must understand in order to be a successful experimental scientist Provides a broad scientific perspective that is perfect for students with various professional backgrounds Contains easily accessible, concise material about diverse methods Includes extensive online resources such as further reading suggestions, data files, statistical tables, and the StaTable application package Emphasizes the ethics and statistics of medical and biological sciences
Research Methodology: A Step by Step Guide for Beginners by
Written specifically for students with no previous experience of research and research methodology, the Third Edition of Research Methodology breaks the process of designing and doing a research project into eight manageable steps and provides plenty of examples throughout to link theory to the practice of doing research. The book contains straightforward, practical guidance on: - Formulating a research question - Ethical considerations - Carrying out a literature review - Choosing a research design - Selecting a sample - Collecting and analysing qualitative and quantitative data - Writing a research report The third edition has been revised and updated to include extended coverage of qualitative research methods in addition to the existing comprehensive coverage of quantitative methods. There are also brand new learning features such as reflective questions throughout the text to help students consolidate their knowledge. The book is essential reading for undergraduate and postgraduate students in the social sciences embarking on qualitative or quantitative research projects.
Research Methods for the Biosciences by 
Understanding Statistics and Experimental Design by 
Writing Research Proposals in the Health Sciences by
This is your step-by-step guide on how to write successful research proposals in the health sciences, whether it is for a thesis or dissertation review committee, an ethical review committee or a grant funding committee. Using quantitative, qualitative, and mixed research approaches, follow the journey of Liang and Natasha, two fictional researchers who will help you complete your proposal alongside reading the chapters. This practical guide includes top tips from the authors, read-reflect-respond activities and examples of project plans to equip you with all the tools you need to succeed with your research proposal.
Experimental Design and Data Analysis for Biologists by
An essential textbook for any student or researcher in biology needing to design experiments, sample programs or analyse the resulting data. The text begins with a revision of estimation and hypothesis testing methods, covering both classical and Bayesian philosophies, before advancing to the analysis of linear and generalized linear models. Topics covered include linear and logistic regression, simple and complex ANOVA models (for factorial, nested, block, split-plot and repeated measures and covariance designs), and log-linear models. Multivariate techniques, including classification and ordination, are then introduced. Special emphasis is placed on checking assumptions, exploratory data analysis and presentation of results. The main analyses are illustrated with many examples from published papers and there is an extensive reference list to both the statistical and biological literature. The book is supported by a website that provides all data sets, questions for each chapter and links to software.
Experimental Design for Biologists by
The effective design and analysis of experiments in biology are critical to success, yet graduate students in biological and medical sciences typically receive very little formal training in these steps. With feedback from readers of the first edition, colleagues, and students taking the very popular experimental design courses taught by the author, this second edition of Experimental Design for Biologists retains the engaging writing style while organizing the book around the four elements of experimental design: the framework, the system, the experiment, and the model. The approach has been tested in the classroom, where the author has taught numerous graduate students, MD/PhD students, and postdoctoral fellows. The goal of every scientist is to discover something new and with the aid of Experimental Design for Biologists, this task is made a little easier. This handbook explains how to establish the framework for an experimental project, how to set up all of the components of an experimental system, design experiments within that system, determine and use the correct set of controls, and formulate models to test the veracity and resiliency of the data. This thoroughly updated edition of Experimental Design for Biologists is an essential source of theory and practical guidance for designing a research plan.
Experimental Design for Laboratory Biologists by
Specifically intended for lab-based biomedical researchers, this practical guide shows how to design experiments that are reproducible, with low bias, high precision, and widely applicable results. With specific examples from research using both cell cultures and model organisms, it explores key ideas in experimental design, assesses common designs, and shows how to plan a successful experiment. It demonstrates how to control biological and technical factors that can introduce bias or add noise, and covers rarely discussed topics such as graphical data exploration, choosing outcome variables, data quality control checks, and data pre-processing. It also shows how to use R for analysis, and is designed for those with no prior experience. An accompanying website (www.cambridge.org/9781107424883) includes all R code, data sets, and the labstats R package. This is an ideal guide for anyone conducting lab-based biological research, from students to principle investigators working in either academia or industry.
Experimental Design for the Life Sciences by 
Choosing and Using Statistics: A Biologist's Guide by
Choosing and Using Statistics remains an invaluable guide for students using a computer package to analyse data from research projects and practical class work. The text takes a pragmatic approach to statistics with a strong focus on what is actually needed. There are chapters giving useful advice on the basics of statistics and guidance on the presentation of data. The book is built around a key to selecting the correct statistical test and then gives clear guidance on how to carry out the test and interpret the output from four commonly used computer packages: SPSS, Minitab, Excel, and (new to this edition) the free program, R. Only the basics of formal statistics are described and the emphasis is on jargon-free English but any unfamiliar words can be looked up in the extensive glossary. This new 3rd edition of Choosing and Using Statistics is a must for all students who use a computer package to apply statistics in practical and project work. Features new to this edition: Now features information on using the popular free program, R Uses a simple key and flow chart to help you choose the right statistical test Aimed at students using statistics for projects and in practical classes Includes an extensive glossary and key to symbols to explain any statistical jargon No previous knowledge of statistics is assumed
Is That a Fact?: A Field Guide to Statistical and Scientific Information by 
Practical Statistics for Field Biology by
Practical Statistics for Field Biology 2E acknowledges the peculiarities of field-based data and its interpretation. It provides students with sufficient grounding in statistical principles and methods to enable them to understand research reports in journals, decide on the most appropriate statistical tests for their own problems, and finally, to analyze and present their findings. To enhance the usefulness of this book, the new edition incorporates the more advanced methods of multivariate analysis, introducing the nature of multivariate problems and describing the techniques of principle components analysis, cluster analysis and discriminant analysis which are all applied to biological examples. An appendix detailing the statistical computing packages available has also been included.
Statistical Methods in Biology by
Written in simple language with relevant examples, Statistical Methods in Biology: Design and Analysis of Experiments and Regressionis a practical and illustrative guide to the design of experiments and data analysis in the biological and agricultural sciences. The book presents statistical ideas in the context of biological and agricultural sciences to which they are being applied, drawing on relevant examples from the authors' experience. Taking a practical and intuitive approach, the book only uses mathematical formulae to formalize the methods where necessary and appropriate. The text features extended discussions of examples that include real data sets arising from research. The authors analyze data in detail to illustrate the use of basic formulae for simple examples while using the GenStat®statistical package for more complex examples. Each chapter offers instructions on how to obtain the example analyses in GenStat and R. By the time you reach the end of the book (and online material) you will have gained: A clear appreciation of the importance of a statistical approach to the design of your experiments, A sound understanding of the statistical methods used to analyse data obtained from designed experiments and of the regression approaches used to construct simple models to describe the observed response as a function of explanatory variables, Sufficient knowledge of how to use one or more statistical packages to analyse data using the approaches described, and most importantly, An appreciation of how to interpret the results of these statistical analyses in the context of the biological or agricultural science within which you are working. The book concludes with a guide to practical design and data analysis. It gives you the understanding to better interact with consultant statisticians and to identify statistical approaches to add value to your scientific research.
Statistics and Scientific Method: An Introduction for Students and Researchers by
Most introductory statistics text-books are written either in a highly mathematical style for an intended readership of mathematics undergraduate students, or in a recipe-book style for an intended audience of non-mathematically inclined undergraduate or postgraduate students, typically in asingle discipline; hence, "statistics for biologists", "statistics for psychologists", and so on.An antidote to technique-oriented service courses, this book is different. It studiously avoids the recipe-book style and keeps algebraic details of specific statistical methods to the minimum extent necessary to understand the underlying concepts. Instead, the text aims to give the reader a clearunderstanding of how core statistical ideas of experimental design, modelling and data analysis are integral to the scientific method. Aimed primarily at beginning postgraduate students across a range of scientific disciplines (albeit with a bias towards the biological, environmental and health sciences), it therefore assumes some maturity of understanding of scientific method, but does not require any prior knowledge ofstatistics, or any mathematical knowledge beyond basic algebra and a willingness to come to terms with mathematical notation.Any statistical analysis of a realistically sized data-set requires the use of specially written computer software. An Appendix introduces the reader to our open-source software of choice, R, whilst the book's web-page includes downloadable data and R code that enables the reader to reproduce all ofthe analyses in the book and, with easy modifications, to adapt the code to analyse their own data if they wish. However, the book is not intended to be a textbook on statistical computing, and all of the material in the book can be understood without using either R or any other computersoftware.
