Biostatistics with R - An Introduction to Statistics Through Biological Data (2012)

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This book will discuss basic statistical analysis methods through a series of biological examples using R and R-Commander as computational tools. The book is intended for a wide range of readers, from people with relatively strong analytical background who want to learn about statistics and its application in biology, to nonstatistician scientists who use statistical methods in their research.
While the theoretical aspects of statistics are intriguing and interesting on their own, we believe that what separates statistics from other branches of mathematics is its intimate relationship with other fields, such as biology, economics, and social sciences, and its widespread application in these areas. In statistics, a theoretical work is usually inspired by applied problems, and new theories usually find immediate applications in real-world problems. This interweaving of theory and application has put statistics in a special place in the scientific world.
In this book, most topics are motivated by real examples first. We believe that learning a new topic becomes easier if it is motivated by interesting and engaging applied problems. We also hope that this approach helps students to improve their critical thinking and problem-solving skills for situations where they are presented with new problems. To this end, we motivate each new topic with a relevant problem from biology. We then try to reach the solution intuitively before discussing the related statistical methods. For example, when discussing Bayes’ theorem, we first present a biological problem (finding the probability of lung cancer for smokers) and find the answer to that problem intuitively based on what we already know. Then, we introduce Bayes’ theorem as a general form of our solution for this type of problem.

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