Core Statistics

Auteur

Simon N. Wood works as a Professor of Statistics at the University of Bath and currently holds an established research fellowship from the Engineering and Physical Sciences Research Council. He is author of the widely used R package mgcv for smooth statistical modelling and the book Generalized Additive Models: An Introduction with R, as well as a number of well-cited papers on associated statistical methods. Originally trained in physics, before a spell in theoretical ecology, he has twenty years' experience of teaching statistics at undergraduate and postgraduate level, including teaching the 'statistical computing' module of the UK Academy for PhD training in statistics, for several years.

Texte du rabat

Core Statistics is a compact starter course on the theory, models, and computational tools needed to make informed use of powerful statistical methods.

Résumé
Core Statistics is a compact starter course on the fundamentals of inference for parametric statistical models, including both theory and practical numerical computation. It delivers the theory and tools that a beginning graduate student, or any quantitative scientist, needs to make informed use of powerful statistical methods.

Contenu

1. Random variables; 2. R; 3. Statistical models and inference; 4. Theory of maximum likelihood estimation; 5. Numerical maximum likelihood estimation; 6. Bayesian computation; 7. Linear models.