Hardback ISBN: 9781108478311
Hardback publication date: 24 June 2021
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Measuring Behaviour
An Introductory Guide
4th edition
, Newcastle University,
Online ISBN: 9781108776462
Online publication date:
07 May 2021
Paperback ISBN: 9781108745727
Paperback publication date: 24 June 2021
- Textbook
Measuring Behaviour is the established go-to text for anyone interested in scientific methods for studying the behaviour of animals or humans. It is widely used by students, teachers and researchers in a variety of fields, including biology, psychology, the social sciences and medicine. This new fourth edition has been completely rewritten and reorganised to reflect major developments in how behavioural studies are conducted. It includes new sections on the replication crisis, covering Open Science initiatives such as preregistration, as well as fully up-to-date information on the use of remote sensors, big data and artificial intelligence in capturing and analysing behaviour. The sections on the analysis and interpretation of data have been rewritten to align with current practices, with advice on avoiding common pitfalls. Although fully revised and revamped, this new edition retains the simplicity, clarity and conciseness that have made Measuring Behaviour a classic since the first edition appeared more than 30 years ago.
Measuring Behaviour is the established go-to text for anyone interested in scientific methods for studying the behaviour of animals or humans. It is widely used by students, teachers and researchers in a variety of fields, including biology, psychology, the social sciences and medicine. This new fourth edition has been completely rewritten and reorganised to reflect major developments in how behavioural studies are conducted. It includes new sections on the replication crisis, covering Open Science initiatives such as preregistration, as well as fully up-to-date information on the use of remote sensors, big data and artificial intelligence in capturing and analysing behaviour. The sections on the analysis and interpretation of data have been rewritten to align with current practices, with advice on avoiding common pitfalls. Although fully revised and revamped, this new edition retains the simplicity, clarity and conciseness that have made Measuring Behaviour a classic since the first edition appeared more than 30 years ago.
A Hands-On Introduction to Data Science with Python
2nd edition
, University of Washington
Coming soon
Online ISBN: 9781009588911
Expected online publication date:
December 2025
Hardback ISBN: 9781009588928
Expected Hardback publication date: 31 December 2025
Paperback ISBN: 9781009588942
Expected Paperback publication date: 31 December 2025
- Textbook
Students will develop a practical understanding of data science with this hands-on textbook for introductory courses. This new edition is fully revised and updated, with numerous exercises and examples in the popular data science tool Python, a new chapter on using Python for statistical analysis, and a new chapter that demonstrates how to use Python within a range of cloud platforms. The many practice examples, drawn from real-life applications, range from small to big data and come to life in a new end-to-end project in Chapter 11. New 'Data Science in Practice' boxes highlight how concepts introduced work within an industry context and many chapters include new sections on AI and Generative AI. A suite of online material for instructors provides a strong supplement to the book, including lecture slides, solutions, additional assessment material and curriculum suggestions. Datasets and code are available for students online. This entry-level textbook is ideal for readers from a range of disciplines wishing to build a practical, working knowledge of data science.
Students will develop a practical understanding of data science with this hands-on textbook for introductory courses. This new edition is fully revised and updated, with numerous exercises and examples in the popular data science tool Python, a new chapter on using Python for statistical analysis, and a new chapter that demonstrates how to use Python within a range of cloud platforms. The many practice examples, drawn from real-life applications, range from small to big data and come to life in a new end-to-end project in Chapter 11. New 'Data Science in Practice' boxes highlight how concepts introduced work within an industry context and many chapters include new sections on AI and Generative AI. A suite of online material for instructors provides a strong supplement to the book, including lecture slides, solutions, additional assessment material and curriculum suggestions. Datasets and code are available for students online. This entry-level textbook is ideal for readers from a range of disciplines wishing to build a practical, working knowledge of data science.
Research Methods in Business Studies
5th edition
, University of Birmingham, , Norwegian School of Economics and Business Administration, Bergen-Sandviken, , University of Sussex
Online ISBN: 9781108762427
Online publication date:
17 January 2020
Hardback ISBN: 9781108486743
Hardback publication date: 12 March 2020
Paperback ISBN: 9781108708241
Paperback publication date: 12 March 2020
This accessible guide provides clear, practical explanations of key research methods in business studies, presenting a step-by-step approach to data collection, analysis and problem solving. Readers will learn how to formulate a research question, choose an appropriate research method, argue and motivate, collect and analyse data, and present findings in a logical and convincing manner. The authors evaluate various qualitative and quantitative methods and their consequences, guiding readers to the most appropriate research design for particular questions. Furthermore, the authors provide instructions on how to write reports and dissertations in a clearly structured and concise style. Now in its fifth edition, this popular textbook includes new and dedicated chapters on data collection for qualitative research, qualitative data analysis, data collection for quantitative research, multiple regression, and additional methods of quantitative analysis. Cases and examples have been updated throughout, increasing the applicability of these research methods across various situations.
This accessible guide provides clear, practical explanations of key research methods in business studies, presenting a step-by-step approach to data collection, analysis and problem solving. Readers will learn how to formulate a research question, choose an appropriate research method, argue and motivate, collect and analyse data, and present findings in a logical and convincing manner. The authors evaluate various qualitative and quantitative methods and their consequences, guiding readers to the most appropriate research design for particular questions. Furthermore, the authors provide instructions on how to write reports and dissertations in a clearly structured and concise style. Now in its fifth edition, this popular textbook includes new and dedicated chapters on data collection for qualitative research, qualitative data analysis, data collection for quantitative research, multiple regression, and additional methods of quantitative analysis. Cases and examples have been updated throughout, increasing the applicability of these research methods across various situations.
Fundamentals of Turbulent Flows
, Stanford University, California, , Stanford University, California
Online ISBN: 9781009431385
Online publication date:
09 January 2025
Hardback ISBN: 9781009431408
Hardback publication date: 06 February 2025
- Textbook
This succinct introduction to the fundamental physical principles of turbulence provides a modern perspective through statistical theory, experiments, and high-fidelity numerical simulations. It describes classical concepts of turbulence and offers new computational perspectives on their interpretation based on numerical simulation databases, introducing students to phenomena at a wide range of scales. Unique, practical, multi-part physics-based exercises use realistic data of canonical turbulent flows developed by the Stanford Center for Turbulence Research to equip students with hands-on experience with practical and predictive analysis tools. Over 20 case studies spanning real-world settings such as wind farms and airplanes, color illustrations, and color-coded pedagogy support student learning. Accompanied by downloadable datasets, and solutions for instructors, this is the ideal introduction for students in aerospace, civil, environmental, and mechanical engineering and the physical sciences studying a graduate-level one-semester course on turbulence, advanced fluid mechanics, and turbulence simulation.
This succinct introduction to the fundamental physical principles of turbulence provides a modern perspective through statistical theory, experiments, and high-fidelity numerical simulations. It describes classical concepts of turbulence and offers new computational perspectives on their interpretation based on numerical simulation databases, introducing students to phenomena at a wide range of scales. Unique, practical, multi-part physics-based exercises use realistic data of canonical turbulent flows developed by the Stanford Center for Turbulence Research to equip students with hands-on experience with practical and predictive analysis tools. Over 20 case studies spanning real-world settings such as wind farms and airplanes, color illustrations, and color-coded pedagogy support student learning. Accompanied by downloadable datasets, and solutions for instructors, this is the ideal introduction for students in aerospace, civil, environmental, and mechanical engineering and the physical sciences studying a graduate-level one-semester course on turbulence, advanced fluid mechanics, and turbulence simulation.
A Hands-On Introduction to Data Science with R
2nd edition
, University of Washington
Coming soon
Online ISBN: 9781009589024
Expected online publication date:
December 2025
Hardback ISBN: 9781009589079
Expected Hardback publication date: 31 December 2025
Paperback ISBN: 9781009589055
Expected Paperback publication date: 31 December 2025
- Textbook
Students will develop a practical understanding of data science with this hands-on textbook for introductory courses. This new edition is fully revised and updated, with numerous exercises and examples in the popular data science tool R, a new chapter on using R for statistical analysis, and a new chapter that demonstrates how to use R within a range of cloud platforms. The many practice examples, drawn from real-life applications, range from small to big data and come to life in a new end-to-end project in Chapter 11. New 'Data Science in Practice' boxes highlight how concepts introduced work within an industry context and many chapters include new sections on AI and Generative AI. A suite of online material for instructors provides a strong supplement to the book, including lecture slides, solutions, additional assessment material and curriculum suggestions. Datasets and code are available for students online. This entry-level textbook is ideal for readers from a range of disciplines wishing to build a practical, working knowledge of data science.
Students will develop a practical understanding of data science with this hands-on textbook for introductory courses. This new edition is fully revised and updated, with numerous exercises and examples in the popular data science tool R, a new chapter on using R for statistical analysis, and a new chapter that demonstrates how to use R within a range of cloud platforms. The many practice examples, drawn from real-life applications, range from small to big data and come to life in a new end-to-end project in Chapter 11. New 'Data Science in Practice' boxes highlight how concepts introduced work within an industry context and many chapters include new sections on AI and Generative AI. A suite of online material for instructors provides a strong supplement to the book, including lecture slides, solutions, additional assessment material and curriculum suggestions. Datasets and code are available for students online. This entry-level textbook is ideal for readers from a range of disciplines wishing to build a practical, working knowledge of data science.
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