Download or read book Statistics at Square One written by Michael J. Campbell and published by John Wiley & Sons. This book was released on 2021-07-13 with total page 307 pages. Available in PDF, EPUB and Kindle. Book excerpt: STATISTICS AT SQUARE ONE The new edition of the popular introduction to the world of statistics for health care professionals and medical students First published nearly three decades ago, Statistics at Square One remains one of the most popular introductions to medical statistics. Now in its twelfth edition, this international bestseller continues to be a must-have resource for anyone in need of a thorough introduction to statistics in the health sciences. Clear and accessible chapters help students with no previous background in the subject understand fundamental topics including summary statistics for quantitative and binary data, diagnostic and screening tests, populations and samples, survival analysis, correlation and regression, study design, computer modeling, and more. This edition reflects contemporary understanding of medical statistics and emphasizes the importance of statistics in public health, including extensively updated coverage of diagnostic tests and new COVID-related examples. All figures and examples now include code to reproduce them in the R statistical software. New chapters cover the basics for understanding numbers and introduce the use of models in medical statistical analysis. Based on the author’s many years of experience teaching medical and health science students, the latest edition of this classic textbook: Highlights the connections between different medical statistics methods Emphasizes the proper use of p-values in testing Features practical examples from recent literature Contains end-of-chapter exercises with answers, some of which are based on the Royal College of General Practitioners (RCGP) Advanced Knowledge Test Statistics at Square One is required reading for all medical and health care practitioners and students wanting to understand the use and value of statistical analysis in the health sciences.