Systematic Reviews

Do you want to know what a parametric test is and when not to perform one? Do you get confused between odds ratios and relative risks? Want to understand the difference between sensitivity and specificity? Would like to find out what the fuss is about Bayes' theorem? Then this book is for you! Physicians need to understand the principles behind medical statistics. They don't need to learn the formula. The software knows it already! This book explains the fundamental concepts of medical statistics so that the learner will become confident in performing the most commonly used statistical tests. Each chapter is rich in anecdotes, illustrations, questions, and answers. Not enough? There is more material online with links to free statistical software, webpages, multimedia content, a practice dataset to get hands-on with data analysis, and a Single Best Answer questionnaire for the exam.

Statistics for Evidence-Based Practice in Nursing, Third Edition promotes a comprehensive understanding of statistics in all aspects of clinical practice and health care settings. This text has been thoughtfully designed to meet the learning needs of practicing nurses and advanced practice nursing students to help them engage in evidence-based practice. Praised for its readability, the Third Edition teaches students to interpret and evaluate statistical findings in practice. The Third Edition is written with clarity and accessibility in mind, helping drive student comprehension of statistics. Expanded datasets allow for learners to take on more complex practice problems, readying them for real-world application. In addition to featuring the latest SPSS procedures, the new edition presents further instruction using Excel. Readers will appreciate updated case studies, the inclusion of evidence-based practice applications of statistics, and critical thinking questions. New to the Third Edition:- New evidence-based case studies reflect current practices and issues in nursing- New critical thinking questions and self-quizzes reinforce key concepts- Complex datasets simulate working with large populations- Updated screenshots from SPSS and Excel procedures

Understanding the underlying principles of statistical techniques and effectively applying statistical methods can be challenging for researchers at all stages of their career. This concise, practical guide uses a simple, engaging approach to take scientists and clinicians working in laboratory-based life science and medical research through the steps of choosing and implementing appropriate statistical methods to analyse results. The author draws on her extensive experience of advising students and researchers over the past 30 years, breaking down complex concepts into easy-to-understand units. Practical examples using free online statistical tools are included throughout, with illustrations and diagrams employed to keep jargon to a minimum. Sample size calculations and considerations are covered in depth, and the book refers to types of data from experiments that clinicians and lab-based scientists are likely to encounter. Straightforward, accessible and encouraging throughout, this is a go-to reference for researchers who want to achieve statistical autonomy.

Statistics are important tools for validating theory, making predictions and engaging in policy research. They help to provide informed commentary about social and environmental issues, and to make the case for change. Knowledge of statistics is therefore a necessary skill for any student of geography or environmental science. This textbook is aimed at students on a degree course taking a module in statistics for the first time. It focuses on analysing, exploring and making sense of data in areas of core interest to physical and human geographers, and to environmental scientists. It covers the subject in a broadly conventional way from descriptive statistics, through inferential statistics to relational statistics but does so with an emphasis on applied data analysis throughout.