e-books in Mathematical Statistics category
by Jonathan A. Poritz - Colorado State University, Pueblo , 2017
This is a first draft of a free textbook for a one-semester, undergraduate statistics course. Contents: One-Variable Statistics - Basics; Bi-variate Statistics - Basics; Linear Regression; Probability Theory; Bringing Home the Data; Basic Inferences.
by Douglas S. Shafer, Zhiyi Zhang - lardbucket.org , 2014
This book is meant to be a textbook for a standard one-semester introductory statistics course for general education students. Our motivation for writing it is to provide a low-cost alternative to many existing popular textbooks on the market.
by David R. Lilja - University of Minnesota , 2016
The book presents one of the fundamental data modeling techniques in an informal tutorial style. Learn how to predict system outputs from measured data using a detailed step-by-step process to develop, train, and test reliable regression models.
by Borek Puza - ANU Press , 2015
A book on statistical methods for analysing a wide variety of data. Topics: bayesian estimation, decision theory, prediction, hypothesis testing, hierarchical models, finite population inference, biased sampling and nonignorable nonresponse, etc.
by Pete Kaslik , 2018
Contents: Statistical Reasoning; Obtaining Useful Evidence; Examining the Evidence Using Graphs and Statistics; Inferential Theory; Testing Hypotheses; Confidence Intervals and Sample Size; Analysis of Bivariate Quantitative Data; Chi Square; etc.
by Ivan Lowe - scientificlanguage.com , 2016
Here I present statistics for the ordinary person. Examples are taken from ordinary life. The book begins with basic concepts behind the statistics and never gets harder than simple arithmetic. The course is presented as a series of key ideas.
by Ivan Lowe - scientificlanguage.com , 2018
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 Stan Brown - BrownMath.com , 2016
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 David Lane - Rice University , 2017
This is a resource for learning and teaching introductory statistics. It contains material presented in textbook format and as video presentations. This resource features interactive demonstrations and simulations, case studies, and an analysis lab.
by Frederic Barbaresco, Frank Nielsen (eds) - MDPI AG , 2017
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 David M Diez, et al. - OpenIntro , 2017
Statistics is an applied field with a wide range of practical applications. This book is geared to the high school audience and is specifically tailored to be aligned with the AP Statistics curriculum. It is already being used by many high schools.
by Walter Antoniotti - 21st Century Learning Products , 2001
Walter Antoniotti's book is for people with a limited mathematics background who want to learn the material covered in a traditional college statistics course and for people who want to learn statistics to enhance their career.
by C.E. Weatherburn - Cambridge University Press , 1961
This book provides the mathematical foundations of statistics. It explains the principles, and proves the formulae to give validity to the methods of the interpretation of statistical data. It is of interest to students of a wide variety of subjects.
by Brian S Blais - Save The Broccoli Publishing , 2014
This is a new approach to an introductory statistical inference textbook, motivated by probability theory as logic. It is targeted to the typical Statistics 101 college student, and covers the topics typically covered in the first semester.
by Miguel A. Hernan, James M. Robins - Chapman & Hall/CRC , 2015
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.
- Wikipedia , 2014
Statistics is the study of the collection, analysis, interpretation, presentation and organization of data. It deals with all aspects of data including the planning of data collection in terms of the design of surveys and experiments.
by Mohammad Saber Fallah Nezhad (ed.) - InTech , 2014
Dynamic programming and Bayesian inference have been both intensively and extensively developed during recent years. The purpose of this volume is to provide some applications of Bayesian optimization and dynamic programming.
by Alex Reinhart - refsmmat.com , 2013
This is a guide to the most popular statistical errors and slip-ups committed by scientists every day, in the lab and in peer-reviewed journals. It assumes no prior knowledge of statistics, you can read it before your first statistics course.
by Darius Singpurwalla - Bookboon , 2013
A Handbook for Statistics provides readers with an overview of common statistical methods used in a wide variety of disciplines. The book focuses on giving the intuition behind the methods as well as how to execute methods using Microsoft Excel.
- Wikibooks , 2013
Statistics is used in almost every field of research. We will learn about subjects in modern statistics and some applications of statistics. We will also lay out some of the background mathematical concepts required to begin studying statistics.
by Henry Lewis Rietz - Open Court Pub. Co , 1927
The book shifts the emphasis in the study of statistics in the direction of the consideration of the underlying theory involved in certain important methods of statistical analysis, and introduces mathematical statistics to a wider range of readers.
by Mohammed A. Shayib - Bookboon , 2013
The book introduces the concepts, definitions, and terminology of the subject in an elementary presentation with a mathematical background which does not surpass college algebra. It should prepare the reader to make a good decision based on data.
by Henk van Elst - arXiv , 2013
These lecture notes were written to provide an accessible though technically solid introduction to the logic of systematical analyses of statistical data to undergraduate and postgraduate students in the Social Sciences and Economics in particular.
by Daniel Navarro - University of Adelaide , 2014
This is an introductory statistics textbook pitched primarily at psychology students. It covers the standard topics of such a book: study design, descriptive statistics, the theory of hypothesis testing, t-tests, X2 tests, ANOVA and regression.
by J.K. Lindsey - Hodder Education Publishers , 1999
Written by a renowned statistician, this book presents the basic ideas behind the statistical methods commonly used in studies of human subjects. It is an ideal guide for advanced undergraduates who are beginning to do their own research.
by Keijo Ruohonen - Tampere University of Technology , 2011
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 Peter Young - arXiv , 2012
These notes discuss, in a style intended for physicists, how to average data and fit it to some functional form. I try to make clear what is being calculated, what assumptions are being made, and to give a derivation of results.
by D.M. Diez, C.D. Barr, M. Cetinkaya-Rundel - OpenIntro , 2012
OpenIntro Statistics is intended for introductory statistics courses at the high school through university levels. There are a large selection of exercises at the end of each chapter useful for practice or homework assignments.
by Howard J. Seltman - Carnegie Mellon University , 2012
This book is intended as required reading material for the course Experimental Design for the Behavioral and Social Sciences, a second level statistics course for undergraduate students in the College of Humanities and Social Sciences...
by Allen B. Downey - Green Tea Press , 2012
Think Bayes is an introduction to Bayesian statistics using computational methods. Contents: Bayes's Theorem; Computational statistics; Tanks and Trains; Urns and Coins; Odds and addends; Hockey; The variability hypothesis; Hypothesis testing.
by Joseph B. Kadane - Chapman and Hall/CRC , 2011
An accessible, comprehensive guide to the theory of Bayesian statistics, this book presents the subjective Bayesian approach, which has played a pivotal role in game theory, economics, and the recent boom in Markov Chain Monte Carlo methods.
by Benjamin Yakir - The Hebrew University of Jerusalem , 2011
This is an introduction to statistics, with R, without calculus. The target audience for this book is college students who are required to learn statistics, students with little background in mathematics and often no motivation to learn more.
by James E. Gentle - George Mason University , 2012
This document is directed toward students for whom mathematical statistics is or will become an important part of their lives. Obviously, such students should be able to work through the details of 'hard' proofs and derivations.
by Philip B. Stark - University of California, Berkeley , 2011
This text was written for an introductory class in Statistics for students in Business, Economics, or Social Science. This is the first and last class in Statistics. It also covers logic and reasoning at a level suitable for a general course.
by Denis Anthony - BookBoon , 2011
This is a practical book. It is aimed at people who need to understand statistics, but not develop it as a subject. The typical reader might be a postgraduate student in health, life, or social science who has no knowledge of statistics.
by Jamie DeCoster - University of Alabama , 1998
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.
by R. Dennis Cook, Sanford Weisberg - Chapman & Hall , 1982
In this monograph, we present a detailed account of the residual based methods that we have found to be most useful, and brief summaries of other selected methods. Our emphasis is on graphical methods rather than on formal testing.
by Michael Falk at al. - University of Wuerzburg , 2011
This book links up elements from time series analysis with a selection of statistical procedures used in general practice including the statistical software package SAS. The book addresses students of statistics, economics, demography, engineering.
by Irving W. Burr - McGraw-Hill , 1953
The present book is the outgrowth of a course in statistics for engineers which has been given at Purdue University. The book is written primarily as a text book for junior, senior, and graduate students of engineering and physical science.
by Hugh D. Young - McGraw Hill , 1962
A concise, highly readable introduction to statistical methods. Even with a limited mathematics background, readers can understand what statistical methods are and how they may be used to obtain the best possible results from experimental data.
by Wolfgang K. Hardle, Leopold Simar - Springer , 2003
The authors present multivariate data analysis in a way that is understandable to non-mathematicians and practitioners confronted by statistical data analysis. The book has a friendly yet rigorous style. Mathematical results are clearly stated.
- NIST/SEMATECH , 2003
The goal of this handbook is to help scientists and engineers incorporate statistical methods in their work as efficiently as possible. Many parts of the book feature case studies or examples with computations from the free downloadable software.
by David W. Stockburger - Missouri State University , 2001
The book for a course in multivariate statistics for first year graduate or advanced undergraduates. It is neither a mathematical treatise nor a cookbook. Instead of complicated mathematical proofs the author wrote about mathematical ideas.
by David W. Stockburger - Missouri State University , 1996
This e-book is a complete interactive study guide with quizzing functionality that reports to the instructor. The on-line text also has animated figures and graphs that bring the print graphic to life for deeper understanding.
by Sidney Tyrrell - BookBoon , 2009
This textbook is for people who want to know how to use SPSS for analyzing data. The author has considerable experience of teaching many such people and assumes they know the basics of statistics but nothing about SPSS, or as it is now known, PASW.
by Marcelo Fernandes - BookBoon , 2009
In today's economic environment it is practically impossible to avoid dealing with data gathering and analysis. This free textbook provides a comprehensive overview of the main topics in the area of statistic analysis for business and economics.
by A. M. Mood, F. A. Graybill, D. C. Boes - McGraw-Hill , 1974
A self contained introduction to classical statistical theory. The material is suitable for students who have successfully completed a single year's course in calculus with no prior knowledge of statistics or probability. Third revised edition.
by T. H. Wonnacott, R. J. Wonnacott - Wiley , 1969
The popular introduction to statistics for students of economics or business. Presents an approach that is generally available only in much more advanced texts, yet uses the simplest mathematics consistent with a sound presentation.
by David Brink - BookBoon , 2008
After reading the theory book about Statistics it is time to test your knowledge to make sure that you are well prepared for your exam. This free exercise book follows the same structure as the theory book about Statistics.
by David Brink - BookBoon , 2008
This compendium of probability and statistics offers an instruction in the central areas of these subjects. The focus is overview. The book is intensively examplefied, which give the reader a recipe how to solve all the common types of exercises.
by Daniel McFadden - University of California, Berkeley , 2001
The contents: Economic Analysis and Econometrics; Analysis and Linear Algebra in a Nutshell; Probability Theory in a Nutshell; Limit Theorems in Statistics; Experiments, Sampling, and Statistical Decisions; Estimation; Hypothesis Testing.
by Ryan Martin - University of Illinois at Chicago , 2015
Table of contents: Statistics and Sampling Distributions; Point Estimation Basics; Likelihood and Maximum Likelihood Estimation; Sufficiency and Minimum Variance Estimation; Hypothesis Testing; Bayesian Statistic; What Else is There to Learn?
by Robert B. Ash - University of Illinois , 2007
These notes are based on a course that the author gave at UIUC. No prior knowledge of statistics is assumed. A standard first course in probability is a prerequisite, but the first 8 lectures review results that are important in statistics.
by David A. Kenny - Little, Brown , 1987
This textbook provides a first course in data analysis for students majoring in the social and behavioral sciences. The book is intended to be comprehensible to students who are not planning to go on to postgraduate study.
by Michael Lavine , 2008
Upper undergraduate or graduate book in statistical thinking for students with a background in calculus and the ability to think abstractly. The focus is on ideas and concepts, as opposed to technical details of how to put those ideas into practice.
by John Verzani - Chapman & Hall/CRC , 2004
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.
by James E. Gentle - Springer , 2009
This book describes computationally-intensive statistical methods in a unified presentation, emphasizing techniques that arise in a wide range of methods. The book assumes an intermediate background in mathematics, computing, and statistics.
by Thomas Hill, Paul Lewicki - StatSoft, Inc. , 2005
A comprehensive statistics textbook for both beginners and advanced analysts. It presents analytic approaches and statistical methods used in science, business, industry, and data mining, written for the real-life practitioner of these methods.
by Barbara Illowsky, Susan Dean - Illowsky Publising , 2012
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 Christian Akrong Hesse - ResearchGate GmbH , 2011
The purpose of this book is to acquaint the reader with the increasing number of applications of statistics in engineering and the applied sciences. Our goal is to introduce the basic theory without getting too involved in mathematical detail.
by D Caradog Jones - G Bell , 1921
First part of the book is within the understanding of the ordinary person. Part 2 is more mathematical, but the results are explained in such a way that the reader shall gain a general idea of the theory and applications without mastering the proofs.
by Richard Lowry , 2008
Free full-length textbook written by a professor of psychology at Vassar College in Poughkeepsie, it offers teachers and students of statistics lots of information. The book covers probability, distribution and correlation, and regression.