Salient features of this book: a unique book for mastering the skills of interpreting various types of data in clinical medicine; useful for postgraduate students to practice and assess their competency in interpreting clinical scenarios; contains 333 case histories and clinical data, 26 spirometry tracings, 14 family trees, 16 data on cardiac catheterization and 171 clinical pictures; relevant clinical information regarding a disease condition have been provided in 'answers' section to help students get a complete idea about the disease without going through voluminous textbooks; helpful for teachers and busy practitioners to quickly refresh their memory; more than enough information for undergraduates and interns.

Here's an essential revision tool for the MRCP exam. The second book in this three-book series, written by renowned experts, offers fully detailed answers and helps to prepare students in data interpretation of laboratory or other results (such as ECGs) by implementing practical case histories.

A practical guide to data-intensive humanities research using the Python programming language The use of quantitative methods in the humanities and related social sciences has increased considerably in recent years, allowing researchers to discover patterns in a vast range of source materials. Despite this growth, there are few resources addressed to students and scholars who wish to take advantage of these powerful tools. Humanities Data Analysis offers the first intermediate-level guide to quantitative data analysis for humanities students and scholars using the Python programming language. This practical textbook, which assumes a basic knowledge of Python, teaches readers the necessary skills for conducting humanities research in the rapidly developing digital environment. The book begins with an overview of the place of data science in the humanities, and proceeds to cover data carpentry: the essential techniques for gathering, cleaning, representing, and transforming textual and tabular data. Then, drawing from real-world, publicly available data sets that cover a variety of scholarly domains, the book delves into detailed case studies. Focusing on textual data analysis, the authors explore such diverse topics as network analysis, genre theory, onomastics, literacy, author attribution, mapping, stylometry, topic modeling, and time series analysis. Exercises and resources for further reading are provided at the end of each chapter. An ideal resource for humanities students and scholars aiming to take their Python skills to the next level, Humanities Data Analysis illustrates the benefits that quantitative methods can bring to complex research questions. Appropriate for advanced undergraduates, graduate students, and scholars with a basic knowledge of Python Applicable to many humanities disciplines, including history, literature, and sociology Offers real-world case studies using publicly available data sets Provides exercises at the end of each chapter for students to test acquired skills Emphasizes visual storytelling via data visualizations

A comprehensive textbook on data analysis for business, applied economics and public policy that uses case studies with real-world data.

First multi-year cumulation covers six years: 1965-70.

This is the authoritative reference work in the field. An interdisciplinary set, it investigates the extensive history, design and methods of case study research.

Providing a complete portal to the world of case study research, the Fourth Edition of Robert K. Yin’s bestselling text Case Study Research offers comprehensive coverage of the design and use of the case study method as a valid research tool. This thoroughly revised text now covers more than 50 case studies (approximately 25% new), gives fresh attention to quantitative analyses, discusses more fully the use of mixed methods research designs, and includes new methodological insights. The book’s coverage of case study research and how it is applied in practice gives readers access to exemplary case studies drawn from a wide variety of academic and applied fields. Key Features of the Fourth Edition Highlights each specific research feature through 44 boxed vignettes that feature previously published case studies Provides methodological insights to show the similarities between case studies and other social science methods Suggests a three-stage approach to help readers define the initial questions they will consider in their own case study research Covers new material on human subjects protection, the role of Institutional Review Boards, and the interplay between obtaining IRB approval and the final development of the case study protocol and conduct of a pilot case Includes an overall graphic of the entire case study research process at the beginning of the book, then highlights the steps in the process through graphics that appear at the outset of all the chapters that follow Offers in-text learning aids including “tips” that pose key questions and answers at the beginning of each chapter, practical exercises, endnotes, and a new cross-referencing table Case Study Research, Fourth Edition is ideal for courses in departments of Education, Business and Management, Nursing and Public Health, Public Administration, Anthropology, Sociology, and Political Science.

In this Handbook, Peter Rule and Vaughn M. John bring together international experts to provide a thorough overview of case study research in the social sciences. Analysing both historical and contemporary examples, the Handbook contains a comprehensive grounding for both experienced and novice researchers in case study theory and methodology, drawing out the challenges as well as the prospects for its development.

In businesses and organizations, understanding the social reality of individuals, groups, and cultures allows for in-depth understanding and rich analysis of multiple research areas to improve practices. Qualitative research provides important insight into the interactions of the workplace. Qualitative Techniques for Workplace Data Analysis is an essential reference source that discusses the qualitative methods used to analyze workplace data, as well as what measures should be adopted to ensure the credibility and dependability of qualitative findings in the workplace. Featuring research on topics such as collection methods, content analysis, and sampling, this book is ideally designed for academicians, development practitioners, business managers, and analytic professionals seeking coverage on quality measurement techniques in the occupational settings of emerging markets.

Based on their own experiences of in-depth case studies of software projects in international corporations, in this book the authors present detailed practical guidelines on the preparation, conduct, design and reporting of case studies of software engineering. This is the first software engineering specific book on the case study research method.