000			00459nam a22001577a 4500
999			_c30716 _d30716
008			180413b2015 xxu||||| |||| 00| 0 eng d
020			_a9781107415041
082			_a519.5 WOO-S
100			_aWood, Simon N.
245			_aCore statistics / _cSimon n. Wood
260			_aNew York _bCambridge University Press _c2015
300			_a250 p.
365			_aGBP _b25.99
500			_aBased on a starter course for beginning graduate students, Core Statistics provides concise coverage of the fundamentals of inference for parametric statistical models, including both theory and practical numerical computation. The book considers both frequentist maximum likelihood and Bayesian stochastic simulation while focusing on general methods applicable to a wide range of models and emphasizing the common questions addressed by the two approaches. This compact package serves as a lively introduction to the theory and tools that a beginning graduate student needs in order to make the transition to serious statistical analysis: inference; modeling; computation, including some numerics; and the R language. Aimed also at any quantitative scientist who uses statistical methods, this book will deepen readers' understanding of why and when methods work and explain how to develop suitable methods for non-standard situations, such as in ecology, big data and genomics.
650			_aStatistics - Text Books
650			_aStatistics - Study and Teaching (Graduate)