Differential Geometrical Theory of Statistics
by Frederic Barbaresco, Frank Nielsen (eds)
Publisher: MDPI AG 2017
Number of pages: 474
Contents: Geometric Thermodynamics of Jean-Marie Souriau; Koszul-Vinberg Model of Hessian Information Geometry; Divergence Geometry and Information Geometry; Density of Probability on manifold and metric space; Statistics on Paths and on Riemannian Manifolds; Entropy and Complexity in Linguistic.
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by Keijo Ruohonen - Tampere University of Technology
Table of contents: Fundamental sampling distributions and data descriptions; One- and two-sample estimation; Tests of hypotheses; X2-tests; Maximum likelihood estimation; Multiple linear regression; Nonparametric statistics; Stochastic simulation.
by Stan Brown - BrownMath.com
This book is an alternative to the usual textbooks for a one-semester course in statistics. The author tried to make statistics approachable to anyone with high-school math, but it's still a technical subject. There is very little use of formulas.
by Barbara Illowsky, Susan Dean - Illowsky Publising
Intended for introductory statistics courses for students at two and four-year colleges who are majoring in fields other than math or engineering. Intermediate algebra is the only prerequisite. The book focuses on applications rather than the theory.
by John Verzani - Chapman & Hall/CRC
A self-contained treatment of statistical topics and the intricacies of the R software. The book focuses on exploratory data analysis, includes chapters on simulation and linear models. It lays the foundation for further study and development using R.