This book is a compact, example-based statistics textbook that closely follows contemporary curricula taught in large parts of the world. It is a user-friendly textbook without unnecessary frills, but instead filled with real-world examples, practical tips, online exercises, resources, and references to extensions, all on a level that is commonly taught at introductory postgraduate and levels. Several features clearly distinguish this book from what is currently available on the market. On the one hand, a lot of the easier textbooks available are lengthy, covering a wide range of topics that are not necessarily taught at university, some including methods that are now rarely used, particularly in the private sector. Further, most texts assume familiarity with statistical software already, and lack a gentle introduction to the specific software that is used. On the other hand, the more specialized textbooks are well outside the reach of most of today’s students, even at postgraduate level, again often assuming a high level of statistical programming skills. This book aims to fill that gap, which, while in its core a traditional printed book, will come with a wealth of online teaching material for lecturers and students. The authors make use of R, quite simply the most used statistics software in science. The content structure is peculiar in the sense that statistical skills are introduced at the same time as software (programming) skills in R. This poses a challenge for students and their lecturers but seems by far the best way of teaching from the author’s experience. By a careful, but concurrent, step by step introduction to both statistical principles and software skills, this text guides the student in an unprecedented way. A color coding system is used to keep the two content matters apart.

R-ticulate: A Beginner’s Guide to Data Analysis for Natural Scientists PDF

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