Pharmaceutical Mathematical Statistics Methods

Author: Liu Dingyuan
Publisher:
Publish Date: 2002-01-01
Features: Medical and Numerical Statistical Methods (3rd Edition) - National Higher Medical Colleges Textbook for Pharmaceutical Majors, edited by Liu Dingyuan, Price: 16.00 yuan
This book is structured around statistical inference, with probability as its foundation and statistical analysis as its application. Chapters 1 to 3 cover the probability foundation of statistics; Chapters 4 to 8 discuss statistical inference methods; Chapters 9 and 10 focus on the statistical analysis of variance and regression models. The 10th and 11th chapters of the second edition have been removed, with the content on sample size estimation merged into relevant parameter estimation and parameter testing. Orthogonal arrays and experimental design have been incorporated into Chapter 9. The probability paper and its applications from the third chapter of the second edition, along with the χ2 test for discrete data from Chapter 6, plus the normality tests for skewness and kurtosis, have been combined into Chapter 7 as goodness-of-fit tests. Chapter 8 on non-parametric tests has been expanded to include multiple comparison rank sum tests and the run test for two samples, enhancing the application scope of non-parametric tests. Additionally, in the probability foundation of statistics, basic concepts such as the hypergeometric distribution, median, and mode have been added.
Given that medical and numerical statistical textbooks must balance the practicality of medical statistics with the theoretical rigor of numerical statistics, the book emphasizes the medical context of statistical concepts through their mathematical definitions during writing. For statistical methods, it combines intuitive explanations with mathematical derivations to analyze their mathematical principles. At the same time, it highlights analytical reasoning and calculation steps through the analysis of medical examples, enhancing the operability of statistical methods. This approach not only facilitates learning and mastery but also better prepares students to correctly select statistical methods, accurately perform statistical calculations, reasonably apply analytical results, and improve their statistical processing skills for medical problems.
Although all three judgment methods for statistical hypothesis testing are discussed, the book primarily focuses on the widely used P-value method in various statistical inference analyses to facilitate understanding. To help students better apply statistical inference analysis and understand statistical computer technology, an appendix titled "Introduction to Common Statistical Analysis Software" has been included at the end of the book. To better encourage students' active learning, summaries are no longer provided for each chapter in this edition.