000			02155nam a22002297a 4500
003			OSt
005			20220726114624.0
008			220726b |||||||| |||| 00| 0 eng d
020			_a9780198827634
040			_ckinley
082			_a519.536 EDG
100			_aEdge, M. D.
245			_aStatistical thinking from scratch : _ba primer for scientists / _cM D Edge.
260			_aOxford : _bOxford University Press, _c2019.
300			_axii, 305 p. : _bill. ; _c24 cm.
504			_aIncludes bibliographical references and index.
520			_a Researchers across the natural and social sciences find themselves navigating tremendous amounts of new data. Making sense of this flood of information requires more than the rote application of formulaic statistical methods. The premise of Statistical Thinking from Scratch is that students who want to become confident data analysts are better served by a deep introduction to a single statistical method than by a cursory overview of many methods. In particular, this book focuses on simple linear regression-a method with close connections to the most important tools in applied statistics-using it as a detailed case study for teaching resampling-based, likelihood-based, and Bayesian approaches to statistical inference. Considering simple linear regression in depth imparts an idea of how statistical procedures are designed, a flavour for the philosophical positions one assumes when applying statistics, and tools to probe the strengths of one's statistical approach. Key to the book's novel approach is its mathematical level, which is gentler than most texts for statisticians but more rigorous than most introductory texts for non-statisticians. Statistical Thinking from Scratch is suitable for senior undergraduate and beginning graduate students, professional researchers, and practitioners seeking to improve their understanding of statistical methods across the natural and social sciences, medicine, psychology, public health, business, and other fields.
650			_a Regression analysis.
650			_aStatistics.
650			_aScience _vStatistical methods.
942			_2ddc _cBK
999			_c15544 _d15544