Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines. The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
All of Statistics
H ̈ardle, W., Hall, P. and Marron, J. S. (1988). How far are automatically chosen regression smoothing parameters from their optimum? Journal of the American Statistical Association 83 86–95. H ̈ardle, W., Kerkyacharian, G., Picard, D.
Following the successful, 'The Humongous Books', in calculus and algebra, bestselling author Mike Kelley takes a typical statistics workbook, full of solved problems, and writes notes in the margins, adding missing steps and simplifying ...
In The Art of Statistics, David Spiegelhalter guides the reader through the essential principles we need in order to derive knowledge from data.
This book presents some of the most important modeling and prediction techniques, along with relevant applications.
... M. H., 367 Maatta, J. M., 447 MacGillivray, H. L., 80 Madansky, A., 447, 459 Mallows, C. L., 369 Marshall, A. W., 121 McCullagh, P., 84 McKean, J. W., 488, 520, 610 McLachlan, G., 370 McPherson, G., 598 Meeden, G., 136, 369 Mendell, ...
The aim of this graduate textbook is to provide a comprehensive advanced course in the theory of statistics covering those topics in estimation, testing, and large sample theory which a graduate student might typically need to learn as ...
This text assumes no previous mathematical or statistical knowledge, taking the reader through each basic technique with step-by-step advice, worked examples, and exercises.
This text assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it.
" Appendices introduce R and Python and contain solutions for odd-numbered exercises. The book's website (http://stat4ds.rwth-aachen.de/) has expanded R, Python, and Matlab appendices and all data sets from the examples and exercises.