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Stats Modeling The World

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Stats

Stats Book
Author : David E. Bock,Paul F. Velleman,Richard D. De Veaux
Publisher : Pearson
Release : 2015-04-23
ISBN : 0134243927
Language : En, Es, Fr & De

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Book Description :

This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. Clear, accessible, and teachable, Stats: Modeling the World leads with practical data analysis and graphics to engage students and get them thinking statistically from the start. Through updated, relevant examples and data—and the authors’ signature Think, Show, and Tell problem-solving method—students learn what we can find in data, why we find it interesting, and how to report it to others. The new Fourth Edition is even more engaging than previous editions, builds on the innovative features that have made the first three editions so popular, and includes revisions designed to make it even easier for students to put the concepts of statistics together in a coherent whole.

Stats

Stats Book
Author : David E. Bock,Paul F. Velleman,Richard D. De Veaux
Publisher : Pearson College Division
Release : 2014-01-14
ISBN : 9780321854018
Language : En, Es, Fr & De

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Book Description :

Normal 0 false false false Clear, accessible, and teachable, "Stats: Modeling the World" leads with practical data analysis and graphics to engage students and get them thinking statistically from the start. Through updated, relevant examples and data--and the authors' signature "Think, Show, and Tell" problem-solving method--students learn what we can find in data, why we find it interesting, and how to report it to others. The new Fourth Edition is even more engaging than previous editions, builds on the innovative features that have made the first three editions so popular, and includes revisions designed to make it even easier for students to put the concepts of statistics together in a coherent whole.

Stats

Stats Book
Author : David E. Bock,Paul F. Velleman,Richard D. De Veaux
Publisher : Pearson
Release : 2007
ISBN : 0987650XXX
Language : En, Es, Fr & De

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Book Description :

By leading with practical data analysis and graphics, "Stats: Modeling the World" gets students " doing statistics" and " thinking statistically" from the start. Students understand what we find in data, why we find it interesting, and how we report it to others as a sound foundation for the challenges of inference. Instructors praise "Stats Modeling the World" as clear and accessible to students, and students report that they enjoy reading the text while learning how to do Statistics with the "Think, Show, "and "Tell "rubric and "What Can Go Wrong?" sections.

Stats in Your World

Stats in Your World Book
Author : David E. Bock,Thomas J. Mariano,William B. Craine,Paul Velleman,Richard D. De Veaux
Publisher : Pearson
Release : 2015-01-01
ISBN : 9780321979513
Language : En, Es, Fr & De

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Book Description :

Download Stats in Your World book written by David E. Bock,Thomas J. Mariano,William B. Craine,Paul Velleman,Richard D. De Veaux, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

Graphing Calculator Manual for Stats

Graphing Calculator Manual for Stats Book
Author : Patricia Humphrey,David E. Bock,John Diehl,Paul F. Velleman,Richard D. De Veaux
Publisher : Addison-Wesley
Release : 2009-03-30
ISBN : 9780321570949
Language : En, Es, Fr & De

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Book Description :

Organized to follow the sequence of topics in the text, this manual is an easy-to-follow, step-by-step guide on how to use the TI-83/84 Plus and TI-89 graphing calculators. It provides worked-out examples to help students fully understand and use their graphing calculator

Regression Modeling Strategies

Regression Modeling Strategies Book
Author : Frank E. Harrell
Publisher : Springer Science & Business Media
Release : 2013-03-09
ISBN : 147573462X
Language : En, Es, Fr & De

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Book Description :

Many texts are excellent sources of knowledge about individual statistical tools, but the art of data analysis is about choosing and using multiple tools. Instead of presenting isolated techniques, this text emphasizes problem solving strategies that address the many issues arising when developing multivariable models using real data and not standard textbook examples. It includes imputation methods for dealing with missing data effectively, methods for dealing with nonlinear relationships and for making the estimation of transformations a formal part of the modeling process, methods for dealing with "too many variables to analyze and not enough observations," and powerful model validation techniques based on the bootstrap. This text realistically deals with model uncertainty and its effects on inference to achieve "safe data mining".

Spatial Statistics and Modeling

Spatial Statistics and Modeling Book
Author : Carlo Gaetan,Xavier Guyon
Publisher : Springer Science & Business Media
Release : 2009-11-10
ISBN : 0387922571
Language : En, Es, Fr & De

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Book Description :

Spatial statistics are useful in subjects as diverse as climatology, ecology, economics, environmental and earth sciences, epidemiology, image analysis and more. This book covers the best-known spatial models for three types of spatial data: geostatistical data (stationarity, intrinsic models, variograms, spatial regression and space-time models), areal data (Gibbs-Markov fields and spatial auto-regression) and point pattern data (Poisson, Cox, Gibbs and Markov point processes). The level is relatively advanced, and the presentation concise but complete. The most important statistical methods and their asymptotic properties are described, including estimation in geostatistics, autocorrelation and second-order statistics, maximum likelihood methods, approximate inference using the pseudo-likelihood or Monte-Carlo simulations, statistics for point processes and Bayesian hierarchical models. A chapter is devoted to Markov Chain Monte Carlo simulation (Gibbs sampler, Metropolis-Hastings algorithms and exact simulation). A large number of real examples are studied with R, and each chapter ends with a set of theoretical and applied exercises. While a foundation in probability and mathematical statistics is assumed, three appendices introduce some necessary background. The book is accessible to senior undergraduate students with a solid math background and Ph.D. students in statistics. Furthermore, experienced statisticians and researchers in the above-mentioned fields will find the book valuable as a mathematically sound reference. This book is the English translation of Modélisation et Statistique Spatiales published by Springer in the series Mathématiques & Applications, a series established by Société de Mathématiques Appliquées et Industrielles (SMAI).

Statistical Rethinking

Statistical Rethinking Book
Author : Richard McElreath
Publisher : CRC Press
Release : 2018-01-03
ISBN : 1315362619
Language : En, Es, Fr & De

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Book Description :

Statistical Rethinking: A Bayesian Course with Examples in R and Stan builds readers’ knowledge of and confidence in statistical modeling. Reflecting the need for even minor programming in today’s model-based statistics, the book pushes readers to perform step-by-step calculations that are usually automated. This unique computational approach ensures that readers understand enough of the details to make reasonable choices and interpretations in their own modeling work. The text presents generalized linear multilevel models from a Bayesian perspective, relying on a simple logical interpretation of Bayesian probability and maximum entropy. It covers from the basics of regression to multilevel models. The author also discusses measurement error, missing data, and Gaussian process models for spatial and network autocorrelation. By using complete R code examples throughout, this book provides a practical foundation for performing statistical inference. Designed for both PhD students and seasoned professionals in the natural and social sciences, it prepares them for more advanced or specialized statistical modeling. Web Resource The book is accompanied by an R package (rethinking) that is available on the author’s website and GitHub. The two core functions (map and map2stan) of this package allow a variety of statistical models to be constructed from standard model formulas.

Statistical Models

Statistical Models Book
Author : David A. Freedman
Publisher : Cambridge University Press
Release : 2009-04-27
ISBN : 9781139477314
Language : En, Es, Fr & De

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Book Description :

This lively and engaging book explains the things you have to know in order to read empirical papers in the social and health sciences, as well as the techniques you need to build statistical models of your own. The discussion in the book is organized around published studies, as are many of the exercises. Relevant journal articles are reprinted at the back of the book. Freedman makes a thorough appraisal of the statistical methods in these papers and in a variety of other examples. He illustrates the principles of modelling, and the pitfalls. The discussion shows you how to think about the critical issues - including the connection (or lack of it) between the statistical models and the real phenomena. The book is written for advanced undergraduates and beginning graduate students in statistics, as well as students and professionals in the social and health sciences.

Modeling with Data

Modeling with Data Book
Author : Ben Klemens
Publisher : Princeton University Press
Release : 2008-10-06
ISBN : 1400828740
Language : En, Es, Fr & De

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Book Description :

Modeling with Data fully explains how to execute computationally intensive analyses on very large data sets, showing readers how to determine the best methods for solving a variety of different problems, how to create and debug statistical models, and how to run an analysis and evaluate the results. Ben Klemens introduces a set of open and unlimited tools, and uses them to demonstrate data management, analysis, and simulation techniques essential for dealing with large data sets and computationally intensive procedures. He then demonstrates how to easily apply these tools to the many threads of statistical technique, including classical, Bayesian, maximum likelihood, and Monte Carlo methods. Klemens's accessible survey describes these models in a unified and nontraditional manner, providing alternative ways of looking at statistical concepts that often befuddle students. The book includes nearly one hundred sample programs of all kinds. Links to these programs will be available on this page at a later date. Modeling with Data will interest anyone looking for a comprehensive guide to these powerful statistical tools, including researchers and graduate students in the social sciences, biology, engineering, economics, and applied mathematics.

An Introduction to Statistical Learning

An Introduction to Statistical Learning Book
Author : Gareth James,Daniela Witten,Trevor Hastie,Robert Tibshirani
Publisher : Springer Science & Business Media
Release : 2013-06-24
ISBN : 1461471389
Language : En, Es, Fr & De

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Book Description :

An Introduction to Statistical Learning provides an accessible overview of the field of statistical learning, an essential toolset for making sense of the vast and complex data sets that have emerged in fields ranging from biology to finance to marketing to astrophysics in the past twenty years. This book presents some of the most important modeling and prediction techniques, along with relevant applications. Topics include linear regression, classification, resampling methods, shrinkage approaches, tree-based methods, support vector machines, clustering, and more. Color graphics and real-world examples are used to illustrate the methods presented. Since the goal of this textbook is to facilitate the use of these statistical learning techniques by practitioners in science, industry, and other fields, each chapter contains a tutorial on implementing the analyses and methods presented in R, an extremely popular open source statistical software platform. Two of the authors co-wrote The Elements of Statistical Learning (Hastie, Tibshirani and Friedman, 2nd edition 2009), a popular reference book for statistics and machine learning researchers. An Introduction to Statistical Learning covers many of the same topics, but at a level accessible to a much broader audience. This book is targeted at statisticians and non-statisticians alike who wish to use cutting-edge statistical learning techniques to analyze their data. The text assumes only a previous course in linear regression and no knowledge of matrix algebra.

Interpretable Machine Learning

Interpretable Machine Learning Book
Author : Christoph Molnar
Publisher : Lulu.com
Release : 2019
ISBN : 0244768528
Language : En, Es, Fr & De

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Book Description :

Download Interpretable Machine Learning book written by Christoph Molnar, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

R for Data Science

R for Data Science Book
Author : Hadley Wickham,Garrett Grolemund
Publisher : "O'Reilly Media, Inc."
Release : 2016-12-12
ISBN : 1491910364
Language : En, Es, Fr & De

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Book Description :

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You’ll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you’ve learned along the way. You’ll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Statistics 101

Statistics 101 Book
Author : David Borman
Publisher : Simon and Schuster
Release : 2018-12-18
ISBN : 1507208189
Language : En, Es, Fr & De

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Book Description :

A comprehensive guide to statistics—with information on collecting, measuring, analyzing, and presenting statistical data—continuing the popular 101 series. Data is everywhere. In the age of the internet and social media, we’re responsible for consuming, evaluating, and analyzing data on a daily basis. From understanding the percentage probability that it will rain later today, to evaluating your risk of a health problem, or the fluctuations in the stock market, statistics impact our lives in a variety of ways, and are vital to a variety of careers and fields of practice. Unfortunately, most statistics text books just make us want to take a snooze, but with Statistics 101, you’ll learn the basics of statistics in a way that is both easy-to-understand and apply. From learning the theory of probability and different kinds of distribution concepts, to identifying data patterns and graphing and presenting precise findings, this essential guide can help turn statistical math from scary and complicated, to easy and fun. Whether you are a student looking to supplement your learning, a worker hoping to better understand how statistics works for your job, or a lifelong learner looking to improve your grasp of the world, Statistics 101 has you covered.

Linear Models in Statistics

Linear Models in Statistics Book
Author : Alvin C. Rencher,G. Bruce Schaalje
Publisher : John Wiley & Sons
Release : 2008-01-18
ISBN : 0470192607
Language : En, Es, Fr & De

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Book Description :

The essential introduction to the theory and application of linear models—now in a valuable new edition Since most advanced statistical tools are generalizations of the linear model, it is neces-sary to first master the linear model in order to move forward to more advanced concepts. The linear model remains the main tool of the applied statistician and is central to the training of any statistician regardless of whether the focus is applied or theoretical. This completely revised and updated new edition successfully develops the basic theory of linear models for regression, analysis of variance, analysis of covariance, and linear mixed models. Recent advances in the methodology related to linear mixed models, generalized linear models, and the Bayesian linear model are also addressed. Linear Models in Statistics, Second Edition includes full coverage of advanced topics, such as mixed and generalized linear models, Bayesian linear models, two-way models with empty cells, geometry of least squares, vector-matrix calculus, simultaneous inference, and logistic and nonlinear regression. Algebraic, geometrical, frequentist, and Bayesian approaches to both the inference of linear models and the analysis of variance are also illustrated. Through the expansion of relevant material and the inclusion of the latest technological developments in the field, this book provides readers with the theoretical foundation to correctly interpret computer software output as well as effectively use, customize, and understand linear models. This modern Second Edition features: New chapters on Bayesian linear models as well as random and mixed linear models Expanded discussion of two-way models with empty cells Additional sections on the geometry of least squares Updated coverage of simultaneous inference The book is complemented with easy-to-read proofs, real data sets, and an extensive bibliography. A thorough review of the requisite matrix algebra has been addedfor transitional purposes, and numerous theoretical and applied problems have been incorporated with selected answers provided at the end of the book. A related Web site includes additional data sets and SAS® code for all numerical examples. Linear Model in Statistics, Second Edition is a must-have book for courses in statistics, biostatistics, and mathematics at the upper-undergraduate and graduate levels. It is also an invaluable reference for researchers who need to gain a better understanding of regression and analysis of variance.

The Book of Why

The Book of Why Book
Author : Judea Pearl,Dana Mackenzie
Publisher : Basic Books
Release : 2018-05-15
ISBN : 0465097618
Language : En, Es, Fr & De

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Book Description :

A Turing Award-winning computer scientist and statistician shows how understanding causality has revolutionized science and will revolutionize artificial intelligence "Correlation is not causation." This mantra, chanted by scientists for more than a century, has led to a virtual prohibition on causal talk. Today, that taboo is dead. The causal revolution, instigated by Judea Pearl and his colleagues, has cut through a century of confusion and established causality -- the study of cause and effect -- on a firm scientific basis. His work explains how we can know easy things, like whether it was rain or a sprinkler that made a sidewalk wet; and how to answer hard questions, like whether a drug cured an illness. Pearl's work enables us to know not just whether one thing causes another: it lets us explore the world that is and the worlds that could have been. It shows us the essence of human thought and key to artificial intelligence. Anyone who wants to understand either needs The Book of Why.

Forecasting principles and practice

Forecasting  principles and practice Book
Author : Rob J Hyndman,George Athanasopoulos
Publisher : OTexts
Release : 2018-05-08
ISBN : 0987507117
Language : En, Es, Fr & De

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Book Description :

Forecasting is required in many situations. Stocking an inventory may require forecasts of demand months in advance. Telecommunication routing requires traffic forecasts a few minutes ahead. Whatever the circumstances or time horizons involved, forecasting is an important aid in effective and efficient planning. This textbook provides a comprehensive introduction to forecasting methods and presents enough information about each method for readers to use them sensibly.

Regression and Other Stories

Regression and Other Stories Book
Author : Andrew Gelman,Jennifer Hill,Aki Vehtari
Publisher : Cambridge University Press
Release : 2020-07-31
ISBN : 110702398X
Language : En, Es, Fr & De

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Book Description :

A practical approach to using regression and computation to solve real-world problems of estimation, prediction, and causal inference.

STATS Modeling the World

STATS Modeling the World Book
Author : Bock,Paul F. Velleman,Richard D. De Veaux
Publisher : Ingram
Release : 2007
ISBN : 9780131876231
Language : En, Es, Fr & De

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Book Description :

Download STATS Modeling the World book written by Bock,Paul F. Velleman,Richard D. De Veaux, available in PDF, EPUB, and Kindle, or read full book online anywhere and anytime. Compatible with any devices.

OpenIntro Statistics

OpenIntro Statistics Book
Author : David Diez,Christopher Barr,Mine Çetinkaya-Rundel
Publisher : Unknown
Release : 2015-07-02
ISBN : 9781943450046
Language : En, Es, Fr & De

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Book Description :

The OpenIntro project was founded in 2009 to improve the quality and availability of education by producing exceptional books and teaching tools that are free to use and easy to modify. We feature real data whenever possible, and files for the entire textbook are freely available at openintro.org. Visit our website, openintro.org. We provide free videos, statistical software labs, lecture slides, course management tools, and many other helpful resources.