The fundamentals of statistical reasoning and applications of data analysis in the realm of biological sciences, including some relatively new methods in statistics (e.g., the use of information criteria and multi-model inference) are the focus of this introductory statistical course. Starting with the most fundamental concepts of probability and statistics, students gradually learn how to correctly apply the common statistical techniques used in experimental biology. This covers accurate experimental planning and sampling as well as accurate statistical analysis interpretation. The curriculum of the course is structured to meet the needs of students who are evaluating data for their own projects, particularly those who are writing theses. With the statistical software R, data analysis practical abilities are developed.
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Andy Hector, The New Statistics with R: an Introduction for Biologists, Oxford University Press, 2015..
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Susan Holmes & Wolfgang Huber, Modern Statistics for Modern Biology, Cambridge University Press, 2019 (also available in an online form at https://web.stanford.edu/class/bios221/book/).
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Wim P. Krijnen, Applied Statistics for Bioinformatics using R, Hanze University, Groningen, NL, 2009.
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