Modern biological data analysis

The book focuses on regression models, specifically univariate generalized linear models (GLM). It is intended primarily for students and colleagues from biological disciplines and requires only basic statistical education, such as one-semester course in biostatistics. The book contains the necessary minimum of statistical theory, but above all, solutions to 18 real-life examples from the field of biology. Each example is developed from description and goal setting through the development of a statistical model to the conclusion. The popular and freely available statistical software R is used for data analysis. The authors deliberately selected the examples to highlight various problems and errors that may occur during data analysis. At the same time, they are intended to motivate readers on how to think about statistical models and how to use them. The reader can try solving the examples on the data supplied with the book. From the authors' Foreword: " After eleven years, we decided to prepare a second edition of the first volume. " This is a revised edition, both conceptually and in content. Innovation is primarily associated with a more sophisticated interpretation of the material. During our 11 years of teaching, we have discovered which things are difficult for students to understand, or what is missing in the book. We tried to explain this better, or rather, to supplement. The biggest change is the shortening of Chapter 5, originally disproportionately long, by moving some of its parts to other chapters. We believe that this will also improve the overall understanding of the theory. R software has evolved and grown considerably over the past 11 years. Both in meaning and content. It is currently one of the leading statistical software tools. Its use for statistical analysis, data preparation, and supporting calculations is now taught at many universities and has become a standard in biology, for example. ” …