Concise Encyclopedia Of Biostatistics For Medical Professionals

Concise Encyclopedia of Biostatistics for Medical Professionals focuses on conceptual knowledge and practical advice rather than mathematical details, enhancing its usefulness as a reference for medical professionals. The book defines and describes nearly 1000 commonly and not so commonly used biostatistical terms and methods arranged in alphabetical order. These range from simple terms, such as mean and median to advanced terms such as multilevel models and generalized estimating equations. Synonyms or alternative phrases for each topic covered are listed with a reference to the topic.

Concise Encyclopedia of Biostatistics for Medical Professionals focuses on conceptual knowledge and practical advice rather than mathematical details, enhancing its usefulness as a reference for medical professionals. The book defines and describes nearly 1000 commonly and not so commonly used biostatistical terms and methods arranged in alphabetical order. These range from simple terms, such as mean and median to advanced terms such as multilevel models and generalized estimating equations. Synonyms or alternative phrases for each topic covered are listed with a reference to the topic.

Encyclopedic in breadth, yet practical and concise, Medical Biostatistics, Fourth Edition focuses on the statistical aspects ofmedicine with a medical perspective, showing the utility of biostatistics as a tool to manage many medical uncertainties. This edition includes more topics in order to fill gaps in the previous edition. Various topics have been enlarged and modified as per the new understanding of the subject.

Clear and user-friendly A-Z format, in handy a pocket size, allows speedy access to information in all settings Fully updated and expanded to cover over 500 statistical terms for comprehensive coverage Enhanced explanations of statistical concepts and methods, including more illustrative content, for greater accessibility Frequent use of examples from the medical literature, with reference to landmark studies, ensures clinical relevance Those new to medical statistics and the more experienced reader will find something of interest here

THIS TEXTBOOK IS A COMPREHENSIVE USER FRIENDLY AND EASY TO READ RESOURCE ON BIOSTATISTICS AND RESEARCH METHODOLOGY. IT IS MEANT FOR UNDERGRADUATE AND POSTGRADUATE MEDICAL STUDENTS AND ALLIED BIOMEDICAL SCIENCES. HEALTH RESEARCHERS, RESEARCH SUPERVISORS AND FACULTY MEMBERS MAY FIND IT USEFUL AS A REFERENCE BOOK

This book discusses the why and how of each step of data-based medical research that can provide basic information to emerging researchers and medical graduate students who write theses or publish articles. The chapters are arranged in the sequence of steps for data-based research. The research steps are comprehensively covered from the selection of the topic to the final publication. Reporting methods such as CONSORT, STARD, and SAMPL guidelines are also covered. Each chapter has separately earmarked examples from the contemporary literature that illustrate the different research methods. Key Features Discusses all the steps of data-based medical research Examines the topics in depth by way of examples from contemporary literature Features notable information in boxes for special attention .

This unique textbook intersects traditional library science with data science principles that readers will find useful in implementing or improving data services within their libraries. Data Science for Librarians introduces data science to students and practitioners in library services. Writing for academic, public, and school library managers; library science students; and library and information science educators, authors Yunfei Du and Hammad Rauf Khan provide a thorough overview of conceptual and practical tools for data librarian practice. Partially due to how quickly data science evolves, libraries have yet to recognize core competencies and skills required to perform the job duties of a data librarian. As society transitions from the information age into the era of big data, librarians and information professionals require new knowledge and skills to stay current and take on new job roles, such as data librarianship. Such skills as data curation, research data management, statistical analysis, business analytics, visualization, smart city data, and learning analytics are relevant in library services today and will become increasingly so in the near future. This text serves as a tool for library and information science students and educators working on data science curriculum design.