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Introduction to the New Statistics

Introduction to the New Statistics PDF Author: Geoff Cumming
Publisher: Routledge
ISBN: 1317483375
Category : Psychology
Languages : en
Pages : 564

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Book Description
This is the first introductory statistics text to use an estimation approach from the start to help readers understand effect sizes, confidence intervals (CIs), and meta-analysis (‘the new statistics’). It is also the first text to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research. In addition, the book explains NHST fully so students can understand published research. Numerous real research examples are used throughout. The book uses today’s most effective learning strategies and promotes critical thinking, comprehension, and retention, to deepen users’ understanding of statistics and modern research methods. The free ESCI (Exploratory Software for Confidence Intervals) software makes concepts visually vivid, and provides calculation and graphing facilities. The book can be used with or without ESCI. Other highlights include: - Coverage of both estimation and NHST approaches, and how to easily translate between the two. - Some exercises use ESCI to analyze data and create graphs including CIs, for best understanding of estimation methods. -Videos of the authors describing key concepts and demonstrating use of ESCI provide an engaging learning tool for traditional or flipped classrooms. -In-chapter exercises and quizzes with related commentary allow students to learn by doing, and to monitor their progress. -End-of-chapter exercises and commentary, many using real data, give practice for using the new statistics to analyze data, as well as for applying research judgment in realistic contexts. -Don’t fool yourself tips help students avoid common errors. -Red Flags highlight the meaning of "significance" and what p values actually mean. -Chapter outlines, defined key terms, sidebars of key points, and summarized take-home messages provide a study tool at exam time. -http://www.routledge.com/cw/cumming offers for students: ESCI downloads; data sets; key term flashcards; tips for using SPSS for analyzing data; and videos. For instructors it offers: tips for teaching the new statistics and Open Science; additional homework exercises; assessment items; answer keys for homework and assessment items; and downloadable text images; and PowerPoint lecture slides. Intended for introduction to statistics, data analysis, or quantitative methods courses in psychology, education, and other social and health sciences, researchers interested in understanding the new statistics will also appreciate this book. No familiarity with introductory statistics is assumed.

Introduction to the New Statistics

Introduction to the New Statistics PDF Author: Geoff Cumming
Publisher: Routledge
ISBN: 1317483375
Category : Psychology
Languages : en
Pages : 564

View

Book Description
This is the first introductory statistics text to use an estimation approach from the start to help readers understand effect sizes, confidence intervals (CIs), and meta-analysis (‘the new statistics’). It is also the first text to explain the new and exciting Open Science practices, which encourage replication and enhance the trustworthiness of research. In addition, the book explains NHST fully so students can understand published research. Numerous real research examples are used throughout. The book uses today’s most effective learning strategies and promotes critical thinking, comprehension, and retention, to deepen users’ understanding of statistics and modern research methods. The free ESCI (Exploratory Software for Confidence Intervals) software makes concepts visually vivid, and provides calculation and graphing facilities. The book can be used with or without ESCI. Other highlights include: - Coverage of both estimation and NHST approaches, and how to easily translate between the two. - Some exercises use ESCI to analyze data and create graphs including CIs, for best understanding of estimation methods. -Videos of the authors describing key concepts and demonstrating use of ESCI provide an engaging learning tool for traditional or flipped classrooms. -In-chapter exercises and quizzes with related commentary allow students to learn by doing, and to monitor their progress. -End-of-chapter exercises and commentary, many using real data, give practice for using the new statistics to analyze data, as well as for applying research judgment in realistic contexts. -Don’t fool yourself tips help students avoid common errors. -Red Flags highlight the meaning of "significance" and what p values actually mean. -Chapter outlines, defined key terms, sidebars of key points, and summarized take-home messages provide a study tool at exam time. -http://www.routledge.com/cw/cumming offers for students: ESCI downloads; data sets; key term flashcards; tips for using SPSS for analyzing data; and videos. For instructors it offers: tips for teaching the new statistics and Open Science; additional homework exercises; assessment items; answer keys for homework and assessment items; and downloadable text images; and PowerPoint lecture slides. Intended for introduction to statistics, data analysis, or quantitative methods courses in psychology, education, and other social and health sciences, researchers interested in understanding the new statistics will also appreciate this book. No familiarity with introductory statistics is assumed.

Introduction to Probability and Statistics

Introduction to Probability and Statistics PDF Author: Dennis V. Lindley
Publisher: CUP Archive
ISBN:
Category : Mathematical statistics
Languages : en
Pages : 259

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Book Description


Introduction to Engineering Statistics and Six Sigma

Introduction to Engineering Statistics and Six Sigma PDF Author: Theodore T. Allen
Publisher: Springer Science & Business Media
ISBN: 1846282004
Category : Technology & Engineering
Languages : en
Pages : 530

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Book Description
This book contains precise descriptions of all of the many related six sigma methods. It also includes many case studies that detail how these methods have been applied in engineering and business to achieve millions of dollars of savings. This book will help readers to determine exactly which methods to apply in which situations and to predict how and when the methods might not be effective. Illustrative examples are provided for all the methods presented and exercises based on the case studies help build associations between techniques and industrial problems.

An Introduction to Probability and Mathematical Statistics

An Introduction to Probability and Mathematical Statistics PDF Author: Howard G. Tucker
Publisher: Academic Press
ISBN: 1483225143
Category : Mathematics
Languages : en
Pages : 240

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Book Description
An Introduction to Probability and Mathematical Statistics provides information pertinent to the fundamental aspects of probability and mathematical statistics. This book covers a variety of topics, including random variables, probability distributions, discrete distributions, and point estimation. Organized into 13 chapters, this book begins with an overview of the definition of function. This text then examines the notion of conditional or relative probability. Other chapters consider Cochran's theorem, which is of extreme importance in that part of statistical inference known as analysis of variance. This book discusses as well the fundamental principles of testing statistical hypotheses by providing the reader with an idea of the basic problem and its relation to practice. The final chapter deals with the problem of estimation and the Neyman theory of confidence intervals. This book is a valuable resource for undergraduate university students who are majoring in mathematics. Students who are majoring in physics and who are inclined toward abstract mathematics will also find this book useful.

Introduction to Applied Bayesian Statistics and Estimation for Social Scientists

Introduction to Applied Bayesian Statistics and Estimation for Social Scientists PDF Author: Scott M. Lynch
Publisher: Springer Science & Business Media
ISBN: 0387712658
Category : Social Science
Languages : en
Pages : 359

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Book Description
This book outlines Bayesian statistical analysis in great detail, from the development of a model through the process of making statistical inference. The key feature of this book is that it covers models that are most commonly used in social science research - including the linear regression model, generalized linear models, hierarchical models, and multivariate regression models - and it thoroughly develops each real-data example in painstaking detail.

Introduction to Bayesian Statistics

Introduction to Bayesian Statistics PDF Author: William M. Bolstad
Publisher: John Wiley & Sons
ISBN: 1118593154
Category : Mathematics
Languages : en
Pages : 624

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Book Description
"...this edition is useful and effective in teaching Bayesian inference at both elementary and intermediate levels. It is a well-written book on elementary Bayesian inference, and the material is easily accessible. It is both concise and timely, and provides a good collection of overviews and reviews of important tools used in Bayesian statistical methods." There is a strong upsurge in the use of Bayesian methods in applied statistical analysis, yet most introductory statistics texts only present frequentist methods. Bayesian statistics has many important advantages that students should learn about if they are going into fields where statistics will be used. In this third Edition, four newly-added chapters address topics that reflect the rapid advances in the field of Bayesian statistics. The authors continue to provide a Bayesian treatment of introductory statistical topics, such as scientific data gathering, discrete random variables, robust Bayesian methods, and Bayesian approaches to inference for discrete random variables, binomial proportions, Poisson, and normal means, and simple linear regression. In addition, more advanced topics in the field are presented in four new chapters: Bayesian inference for a normal with unknown mean and variance; Bayesian inference for a Multivariate Normal mean vector; Bayesian inference for the Multiple Linear Regression Model; and Computational Bayesian Statistics including Markov Chain Monte Carlo. The inclusion of these topics will facilitate readers' ability to advance from a minimal understanding of Statistics to the ability to tackle topics in more applied, advanced level books. Minitab macros and R functions are available on the book's related website to assist with chapter exercises. Introduction to Bayesian Statistics, Third Edition also features: Topics including the Joint Likelihood function and inference using independent Jeffreys priors and join conjugate prior The cutting-edge topic of computational Bayesian Statistics in a new chapter, with a unique focus on Markov Chain Monte Carlo methods Exercises throughout the book that have been updated to reflect new applications and the latest software applications Detailed appendices that guide readers through the use of R and Minitab software for Bayesian analysis and Monte Carlo simulations, with all related macros available on the book's website Introduction to Bayesian Statistics, Third Edition is a textbook for upper-undergraduate or first-year graduate level courses on introductory statistics course with a Bayesian emphasis. It can also be used as a reference work for statisticians who require a working knowledge of Bayesian statistics.

Using Statistics: A Gentle Introduction

Using Statistics: A Gentle Introduction PDF Author: Rugg, Gordon
Publisher: McGraw-Hill Education (UK)
ISBN: 0335222188
Category : Education
Languages : en
Pages : 137

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Book Description
An introduction to statistics covers the concepts measurement theory, descriptive statistics, knowlege reprensentation, probability theory, correlations, and parametric statistics.

Introduction to Statistics

Introduction to Statistics PDF Author: A.W Bowman
Publisher: CRC Press
ISBN: 9780852744086
Category : Mathematics
Languages : en
Pages : 205

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Book Description
In a clear and entertaining way, An Introduction to Statistics explains the basic principles and the more commonly used techniques of statistics. The text describes each topic and method usually through examples drawn from a wide range of applications of statistics. Key results are gathered together and statistical tables are provided for ease of reference. The software produces graphical displays that demonstrate ideas and methods as they are introduced in the text. These displays have the advantage over traditional diagrams because they are colorful, animated, and, most importantly, interactive. No knowledge of programming is necessary and readers can test a demonstration numerous times and, by modifying parameters or data, can compare results and acquire a fuller grasp of the points being made. This computer-illustrated package is intended for students of any age who are undertaking a first course in statistics or who have some basic knowledge but wish to expand their understanding in a simple and pleasurable manner. Teachers can also make use of the software for class demonstrations and tutorial purposes. The book is appropriate for anyone who wishes to learn or revise material on statistical techniques, including research workers in many areas of science and professionals who use statistical data in business or everyday life.

Introduction to Statistics for Nurses

Introduction to Statistics for Nurses PDF Author: John Maltby
Publisher: Pearson Education
ISBN: 9780131967533
Category : Mathematics
Languages : en
Pages : 268

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Book Description
Take the fear out of statistics with this straightforward, practical and applied book on the 'how and why' of using statistics. Introduction to Statistics for Nurses is an essential introductory text for all nursing students coming to statistics for the first time. The nursing profession involves the use of statistics every day, for example in the cases of mortality rates, average life expectancies, percentage recovery rates, average remission times, and the findings of which drugs work best with which illnesses. In fact, all of the policies that surround this job, the treatment strategies, and all the facts described above are derived from the use of statistics. This book will help students to understand the use of statistics in nursing literature, and shows how to use statistics effectively in answering research questions. Case studies throughout show how statistics are applied in nursing research and frequent exercises help to test the reader's knowledge as they progress.

Introduction to Probability and Statistics for Ecosystem Managers

Introduction to Probability and Statistics for Ecosystem Managers PDF Author: Timothy C. Haas
Publisher: John Wiley & Sons
ISBN: 1118636236
Category : Mathematics
Languages : en
Pages : 312

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Book Description
Explores computer-intensive probability and statistics for ecosystem management decision making Simulation is an accessible way to explain probability and stochastic model behavior to beginners. This book introduces probability and statistics to future and practicing ecosystem managers by providing a comprehensive treatment of these two areas. The author presents a self-contained introduction for individuals involved in monitoring, assessing, and managing ecosystems and features intuitive, simulation-based explanations of probabilistic and statistical concepts. Mathematical programming details are provided for estimating ecosystem model parameters with Minimum Distance, a robust and computer-intensive method. The majority of examples illustrate how probability and statistics can be applied to ecosystem management challenges. There are over 50 exercises – making this book suitable for a lecture course in a natural resource and/or wildlife management department, or as the main text in a program of self-study. Key features: Reviews different approaches to wildlife and ecosystem management and inference. Uses simulation as an accessible way to explain probability and stochastic model behavior to beginners. Covers material from basic probability through to hierarchical Bayesian models and spatial/ spatio-temporal statistical inference. Provides detailed instructions for using R, along with complete R programs to recreate the output of the many examples presented. Provides an introduction to Geographic Information Systems (GIS) along with examples from Quantum GIS, a free GIS software package. A companion website featuring all R code and data used throughout the book. Solutions to all exercises are presented along with an online intelligent tutoring system that supports readers who are using the book for self-study.