Elementary Statistical Methods
by Christian Akrong Hesse
Publisher: ResearchGate GmbH 2011
Number of pages: 83
The purpose of this book is to acquaint the reader with the increasing number of applications of statistics in engineering and the applied sciences. It can be used as a textbook for a first course in statistical methods in Universities and Polytechnics. Our goal is to introduce the basic theory without getting too involved in mathematical detail, and thus to enable a larger proportion of the book to be devoted to practical applications.
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by Frederic Barbaresco, Frank Nielsen (eds) - MDPI AG
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 Manifolds; etc.
by Ivan Lowe - scientificlanguage.com
The book begins by expanding on some of the basic concepts such data types and variables. The basic choice then is between the family of statistics which compares groups, and the family which studies associations or correlations.
by Miguel A. Hernan, James M. Robins - Chapman & Hall/CRC
The book provides a cohesive presentation of concepts of, and methods for, causal inference. It will be of interest to anyone interested in causal inference, e.g., epidemiologists, statisticians, psychologists, economists, sociologists, and others.
by Jamie DeCoster - University of Alabama
It is important to know how to understand statistics so that we can make the proper judgments when a person presents us with an argument backed by data. Data are numbers with a context. We must always keep the meaning of our data in mind.