Statistical reasoning and modeling are of critical importance to modern biology. This textbook introduces fundamental concepts from probability and statistics which will pave the way for the student of biology to become a well-rounded scientist. No previous study of probability or statistics is assumed. Calculus topics are not used extensively in this book, though some integration and differentiation are expected. The calculus prerequisite is primarily intended to assure a certain level of mathematical maturity.This book puts emphasis on examples, which are presented to motivate the theory. The presentation style is concise and self-contained, briefly including the mathematical elements that are needed for studying probability and statistics. The examples are relevant to students in the life sciences with interests in genetics, biology, ecology, health, etc.We believe that aspects of probability theory are of biological interest and that probability underlies the theory of inferential statistics. Thus, we place an equal emphasis on probability and statistics which are both essential for solving and understanding many types of biological problems.
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The overall approach is sound and provides information on the background of selected statistical tests and how to do them - or not. --The Biologist
The book is self-contained, easy to read, and the presentation style is exact and concise, colorful examples lighten up the dry topic of statistics to the inexperienced reader. I warmly recommend this book to the target readership as a first introduction into the field. --Biometrical Journal
The examples used in the book are kept simple but based on real-life situations and connected to the natural sciences such as genetics, biology, ecology and health. Introducing statistical and probabilistic knowledge through such examples can easily draw students' interest and may open a door for them to apply the knowledge in a more complex situation. Furthermore, a large number of problems are given in each chapter and also in two separate chapters. This provides sufficient examples for students to attempt and extend the knowledge they have just learned, hence leading to a deeper understanding of this subject. In summary, this book is a good introduction to Biostatistics. It is concise, self-contained and suitable as a textbook for students of the life sciences with an interest in Biostatistics and also suitable for those people who want a quick taste of Biostatistics. --Journal of Applied Statistics
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