The ability to interpret and synthesise medical data is essential for doctors, yet it is a skill which can be difficult to master. Data Interpretation Made Easy focuses on developing this skill by presenting an array of case-based themes considering interpretation of blood results, X-rays, ECGs and CT images in medicine with discussion of evidence-based practice. The concise, list-based text aids easy comprehension and images provide the much needed link from raw data to evidence-based care and management. This highly practical book is essential reading for undergraduate medical students preparing for examinations. It is also ideal for junior doctors needing a succinct guide to data interpretation for everyday use. 'Dr Neel Sharma's latest venture on data interpretation has dozens of credible clinical scenarios covering many key areas of clinical medicine. And you will certainly feel challenged, as he leaves it up to you to diagnose and devise the treatment plan.' From the Foreword by Tiago Villanueva

The ability to interpret and synthesise medical data is essential for doctors, yet it is a skill which can be difficult to master. Data Interpretation Made Easy focuses on developing this skill by presenting an array of case-based themes considering interpretation of blood results, X-rays, ECGs and CT images in medicine with discussion of evidence-based practice. The concise, list-based text aids easy comprehension and images provide the much needed link from raw data to evidence-based care and management. This highly practical book is essential reading for undergraduate medical students pr.

Make your data sing with data visualization. In today's data-driven world, it's more important than ever to be able to communicate data effectively. Data visualization is the art of transforming data into visually appealing charts, graphs, and dashboards that convey your message clearly and persuasively. Data Visualization Made Easy is the perfect resource for anyone who wants to learn how to use data visualization to communicate their data. This comprehensive guide covers everything you need to know, from the basics of data visualization to advanced topics such as data storytelling and dashboard design. Whether you're a student, a business professional, or a data enthusiast, Data Visualization Made Easy is the essential resource for learning how to communicate data effectively. Here are some of the key topics covered in the book: Introduction to data visualization Choosing the right data visualization Creating effective data visualizations Data storytelling Dashboard design With Data Visualization Made Easy, you'll be well on your way to becoming a data visualization expert.

A guide to reading and understanding rhythm strips and 12-lead ECGs, this updated edition reviews fundamental cardiac anatomy and physiology, explains how to interpret a rhythm strip, and teaches the reader how to recognize and treat 18 arrhythmias.

Data interpretation questions based on clinical cases are a popular means of testing medical students both during undergraduate studies and as an element of finals examinations. Written by a small team of authors with extensive teaching experience, 100 Cases in Medical Data Interpretation provides invaluable guidance from lecturers who understand from personal experience that detailed and accurate explanations are the key to successful revision. This book presents 100 cases arranged by specialty area—radiology, clinical chemistry, haematology and cardiology—as well as a random section of miscellaneous cases. Questions accompanying each case prompt the reader to consider how the data presented might be correctly understood. A clear discussion of how the correct answer was reached, with boxed highlights and bullet lists of key points, makes this book an excellent learning aid during all stages of clinical studies, and particularly while preparing for medical finals.

"Data analysis has become a necessary skill across the social sciences, and recent advancements in computing power have made knowledge of programming an essential component. Yet most data science books are intimidating and overwhelming to a non-specialist audience, including most undergraduates. This book will be a shorter, more focused and accessible version of Kosuke Imai's Quantitative Social Science book, which was published by Princeton in 2018 and has been adopted widely in graduate level courses of the same title. This book uses the same innovative approach as Quantitative Social Science , using real data and 'R' to answer a wide range of social science questions. It assumes no prior knowledge of statistics or coding. It starts with straightforward, simple data analysis and culminates with multivariate linear regression models, focusing more on the intuition of how the math works rather than the math itself. The book makes extensive use of data visualizations, diagrams, pictures, cartoons, etc., to help students understand and recall complex concepts, provides an easy to follow, step-by-step template of how to conduct data analysis from beginning to end, and will be accompanied by supplemental materials in the appendix and online for both students and instructors"--