Introduction to statistical data analysis for the life sciences

•Focuses on applications and computational statistics with a reasonable level of mathematical rigor •Includes a short tutorial for newcomers to R as well as an R section in each chapter •Provides a reference to statistical formulas for various special cases •Contains both standard and computational exercises •Offers the datasets in an R package on CRAN and lecture slides on the authors’ website Expanded with over 100 more pages, Introduction to Statistical Data Analysis for the Life Sciences, Second Edition presents the right balance of data examples, statistical theory, and computing to teach introductory statistics to students in the life sciences. This popular textbook covers the mathematics underlying classical statistical analysis, the modeling aspects of statistical analysis and the biological interpretation of results, and the application of statistical software in analyzing real-world problems and datasets. - This text provides a computational toolbox that enables students to analyze real datasets and gain the confidence and skills to undertake more sophisticated analyses. Although accessible with any statistical software, the text encourages a reliance on R. For those new to R, an introduction to the software is available in an appendix. The book also includes end-of-chapter exercises as well as an entire chapter of case exercises that help students apply their knowledge to larger datasets and learn more about approaches specific to the life sciences.