Author: Barry C. Arnold
Publisher: SIAM
ISBN: 0898716489
Category : Mathematics
Languages : en
Pages : 291
Book Description
This updated classic text will aid readers in understanding much of the current literature on order statistics: a flourishing field of study that is essential for any practising statistician and a vital part of the training for students in statistics. Written in a simple style that requires no advanced mathematical or statistical background, the book introduces the general theory of order statistics and their applications. The book covers topics such as distribution theory for order statistics from continuous and discrete populations, moment relations, bounds and approximations, order statistics in statistical inference and characterisation results, and basic asymptotic theory. There is also a short introduction to record values and related statistics. The authors have updated the text with suggestions for further reading that may be used for self-study. Written for advanced undergraduate and graduate students in statistics and mathematics, practising statisticians, engineers, climatologists, economists, and biologists.
A First Course in Order Statistics
Author: Barry C. Arnold
Publisher: SIAM
ISBN: 0898716489
Category : Mathematics
Languages : en
Pages : 291
Book Description
This updated classic text will aid readers in understanding much of the current literature on order statistics: a flourishing field of study that is essential for any practising statistician and a vital part of the training for students in statistics. Written in a simple style that requires no advanced mathematical or statistical background, the book introduces the general theory of order statistics and their applications. The book covers topics such as distribution theory for order statistics from continuous and discrete populations, moment relations, bounds and approximations, order statistics in statistical inference and characterisation results, and basic asymptotic theory. There is also a short introduction to record values and related statistics. The authors have updated the text with suggestions for further reading that may be used for self-study. Written for advanced undergraduate and graduate students in statistics and mathematics, practising statisticians, engineers, climatologists, economists, and biologists.
Publisher: SIAM
ISBN: 0898716489
Category : Mathematics
Languages : en
Pages : 291
Book Description
This updated classic text will aid readers in understanding much of the current literature on order statistics: a flourishing field of study that is essential for any practising statistician and a vital part of the training for students in statistics. Written in a simple style that requires no advanced mathematical or statistical background, the book introduces the general theory of order statistics and their applications. The book covers topics such as distribution theory for order statistics from continuous and discrete populations, moment relations, bounds and approximations, order statistics in statistical inference and characterisation results, and basic asymptotic theory. There is also a short introduction to record values and related statistics. The authors have updated the text with suggestions for further reading that may be used for self-study. Written for advanced undergraduate and graduate students in statistics and mathematics, practising statisticians, engineers, climatologists, economists, and biologists.
A Casebook for a First Course in Statistics and Data Analysis
Author: Samprit Chatterjee
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 334
Book Description
Containing 61 cases studies from business, the media and the natural and social sciences, this text is organized by broad applicational areas: data analysis; applied probability; inference; and regression models.
Publisher:
ISBN:
Category : Mathematics
Languages : en
Pages : 334
Book Description
Containing 61 cases studies from business, the media and the natural and social sciences, this text is organized by broad applicational areas: data analysis; applied probability; inference; and regression models.
A First Course in Statistics
Author: James T. McClave
Publisher:
ISBN: 9781292023663
Category : Statistics
Languages : en
Pages : 598
Book Description
Classic, yet contemporary. Theoretical, yet applied. McClave & Sincich's Statistics: A First Course in Statistics gives you the best of both worlds. This text offers a trusted, comprehensive introduction to statistics that emphasizes inference and integrates real data throughout. The authors stress the development of statistical thinking, the assessment of credibility, and value of the inferences made from data. The Eleventh Edition infuses a new focus on ethics, which is critically important when working with statistical data. Chapter Summaries have a new, study-oriented design, helping students stay focused when preparing for exams. Data, exercises, technology support, and Statistics in Action cases are updated throughout the book.
Publisher:
ISBN: 9781292023663
Category : Statistics
Languages : en
Pages : 598
Book Description
Classic, yet contemporary. Theoretical, yet applied. McClave & Sincich's Statistics: A First Course in Statistics gives you the best of both worlds. This text offers a trusted, comprehensive introduction to statistics that emphasizes inference and integrates real data throughout. The authors stress the development of statistical thinking, the assessment of credibility, and value of the inferences made from data. The Eleventh Edition infuses a new focus on ethics, which is critically important when working with statistical data. Chapter Summaries have a new, study-oriented design, helping students stay focused when preparing for exams. Data, exercises, technology support, and Statistics in Action cases are updated throughout the book.
Statistical Concepts - A Second Course
Author: Debbie L. Hahs-Vaughn
Publisher: Routledge
ISBN: 113649006X
Category : Psychology
Languages : en
Pages : 534
Book Description
Statistical Concepts consists of the last 9 chapters of An Introduction to Statistical Concepts, 3rd ed. Designed for the second course in statistics, it is one of the few texts that focuses just on intermediate statistics. The book highlights how statistics work and what they mean to better prepare students to analyze their own data and interpret SPSS and research results. As such it offers more coverage of non-parametric procedures used when standard assumptions are violated since these methods are more frequently encountered when working with real data. Determining appropriate sample sizes is emphasized throughout. Only crucial equations are included. The new edition features: New co-author, Debbie L. Hahs-Vaughn, the 2007 recipient of the University of Central Florida's College of Education Excellence in Graduate Teaching Award. A new chapter on logistic regression models for today's more complex methodologies. Much more on computing confidence intervals and conducting power analyses using G*Power. All new SPSS version 19 screenshots to help navigate through the program and annotated output to assist in the interpretation of results. Sections on how to write-up statistical results in APA format and new templates for writing research questions. New learning tools including chapter-opening vignettes, outlines, a list of key concepts, "Stop and Think" boxes, and many more examples, tables, and figures. More tables of assumptions and the effects of their violation including how to test them in SPSS. 33% new conceptual, computational, and all new interpretative problems. A website with Power Points, answers to the even-numbered problems, detailed solutions to the odd-numbered problems, and test items for instructors, and for students the chapter outlines, key concepts, and datasets. Each chapter begins with an outline, a list of key concepts, and a research vignette related to the concepts. Realistic examples from education and the behavioral sciences illustrate those concepts. Each example examines the procedures and assumptions and provides tips for how to run SPSS and develop an APA style write-up. Tables of assumptions and the effects of their violation are included, along with how to test assumptions in SPSS. Each chapter includes computational, conceptual, and interpretive problems. Answers to the odd-numbered problems are provided. The SPSS data sets that correspond to the book’s examples and problems are available on the web. The book covers basic and advanced analysis of variance models and topics not dealt with in other texts such as robust methods, multiple comparison and non-parametric procedures, and multiple and logistic regression models. Intended for courses in intermediate statistics and/or statistics II taught in education and/or the behavioral sciences, predominantly at the master's or doctoral level. Knowledge of introductory statistics is assumed.
Publisher: Routledge
ISBN: 113649006X
Category : Psychology
Languages : en
Pages : 534
Book Description
Statistical Concepts consists of the last 9 chapters of An Introduction to Statistical Concepts, 3rd ed. Designed for the second course in statistics, it is one of the few texts that focuses just on intermediate statistics. The book highlights how statistics work and what they mean to better prepare students to analyze their own data and interpret SPSS and research results. As such it offers more coverage of non-parametric procedures used when standard assumptions are violated since these methods are more frequently encountered when working with real data. Determining appropriate sample sizes is emphasized throughout. Only crucial equations are included. The new edition features: New co-author, Debbie L. Hahs-Vaughn, the 2007 recipient of the University of Central Florida's College of Education Excellence in Graduate Teaching Award. A new chapter on logistic regression models for today's more complex methodologies. Much more on computing confidence intervals and conducting power analyses using G*Power. All new SPSS version 19 screenshots to help navigate through the program and annotated output to assist in the interpretation of results. Sections on how to write-up statistical results in APA format and new templates for writing research questions. New learning tools including chapter-opening vignettes, outlines, a list of key concepts, "Stop and Think" boxes, and many more examples, tables, and figures. More tables of assumptions and the effects of their violation including how to test them in SPSS. 33% new conceptual, computational, and all new interpretative problems. A website with Power Points, answers to the even-numbered problems, detailed solutions to the odd-numbered problems, and test items for instructors, and for students the chapter outlines, key concepts, and datasets. Each chapter begins with an outline, a list of key concepts, and a research vignette related to the concepts. Realistic examples from education and the behavioral sciences illustrate those concepts. Each example examines the procedures and assumptions and provides tips for how to run SPSS and develop an APA style write-up. Tables of assumptions and the effects of their violation are included, along with how to test assumptions in SPSS. Each chapter includes computational, conceptual, and interpretive problems. Answers to the odd-numbered problems are provided. The SPSS data sets that correspond to the book’s examples and problems are available on the web. The book covers basic and advanced analysis of variance models and topics not dealt with in other texts such as robust methods, multiple comparison and non-parametric procedures, and multiple and logistic regression models. Intended for courses in intermediate statistics and/or statistics II taught in education and/or the behavioral sciences, predominantly at the master's or doctoral level. Knowledge of introductory statistics is assumed.
Statistics
Author: Donald H. Sanders
Publisher: McGraw-Hill Science/Engineering/Math
ISBN: 9780072295474
Category : Statistics
Languages : en
Pages : 664
Book Description
The main difference between this text and many others is that an attempt is made here to present material in a rather relaxed and informal way without omitting important concepts. The text demonstrates the wide range of relevant issues and questions that can be addressed with the help of statistical analysis techniques by presenting over 1,750 realistic problems that arise often in health care, the social and physical sciences, education, business and economics, engineering, and leisure activities. It also convinces your students that statistics is "do-able" by including real data that students have collected and analyzed for class assignments and projects. Additionally, the text utilizes an intuitive, common sense approach (including occasional humorous situation or ridiculous name) to develop concepts whenever possible. "Statistics: A First Course" employs widely available, inexpensive technologies--particularly Minitab and the TI-83 graphing calculator. We also explore the use of the World Wide Web to collect data, providing students with the means to obtain up-to-date information without leaving their desks. In short this book is written to communicate with students rather than to lecture to them, and its intent is to convince readers that the study of statistics can be a lively, interesting, and rewarding experience!
Publisher: McGraw-Hill Science/Engineering/Math
ISBN: 9780072295474
Category : Statistics
Languages : en
Pages : 664
Book Description
The main difference between this text and many others is that an attempt is made here to present material in a rather relaxed and informal way without omitting important concepts. The text demonstrates the wide range of relevant issues and questions that can be addressed with the help of statistical analysis techniques by presenting over 1,750 realistic problems that arise often in health care, the social and physical sciences, education, business and economics, engineering, and leisure activities. It also convinces your students that statistics is "do-able" by including real data that students have collected and analyzed for class assignments and projects. Additionally, the text utilizes an intuitive, common sense approach (including occasional humorous situation or ridiculous name) to develop concepts whenever possible. "Statistics: A First Course" employs widely available, inexpensive technologies--particularly Minitab and the TI-83 graphing calculator. We also explore the use of the World Wide Web to collect data, providing students with the means to obtain up-to-date information without leaving their desks. In short this book is written to communicate with students rather than to lecture to them, and its intent is to convince readers that the study of statistics can be a lively, interesting, and rewarding experience!
A First Course in Statistical Programming with R
Author: John Braun
Publisher:
ISBN: 9780521872652
Category : Computers
Languages : en
Pages : 163
Book Description
The only introduction you'll need to start programming in R.
Publisher:
ISBN: 9780521872652
Category : Computers
Languages : en
Pages : 163
Book Description
The only introduction you'll need to start programming in R.
A First Course in Probability and Statistics
Author: B. L. S. Prakasa Rao
Publisher: World Scientific
ISBN: 9812836535
Category : Mathematics
Languages : en
Pages : 330
Book Description
This book provides a clear exposition of the theory of probability along with applications in statistics.
Publisher: World Scientific
ISBN: 9812836535
Category : Mathematics
Languages : en
Pages : 330
Book Description
This book provides a clear exposition of the theory of probability along with applications in statistics.
A First Course in Bayesian Statistical Methods
Author: Peter D. Hoff
Publisher: Springer Science & Business Media
ISBN: 0387924078
Category : Mathematics
Languages : en
Pages : 270
Book Description
A self-contained introduction to probability, exchangeability and Bayes’ rule provides a theoretical understanding of the applied material. Numerous examples with R-code that can be run "as-is" allow the reader to perform the data analyses themselves. The development of Monte Carlo and Markov chain Monte Carlo methods in the context of data analysis examples provides motivation for these computational methods.
Publisher: Springer Science & Business Media
ISBN: 0387924078
Category : Mathematics
Languages : en
Pages : 270
Book Description
A self-contained introduction to probability, exchangeability and Bayes’ rule provides a theoretical understanding of the applied material. Numerous examples with R-code that can be run "as-is" allow the reader to perform the data analyses themselves. The development of Monte Carlo and Markov chain Monte Carlo methods in the context of data analysis examples provides motivation for these computational methods.
The Book of R
Author: Tilman M. Davies
Publisher: No Starch Press
ISBN: 1593276516
Category : Computers
Languages : en
Pages : 833
Book Description
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.
Publisher: No Starch Press
ISBN: 1593276516
Category : Computers
Languages : en
Pages : 833
Book Description
The Book of R is a comprehensive, beginner-friendly guide to R, the world’s most popular programming language for statistical analysis. Even if you have no programming experience and little more than a grounding in the basics of mathematics, you’ll find everything you need to begin using R effectively for statistical analysis. You’ll start with the basics, like how to handle data and write simple programs, before moving on to more advanced topics, like producing statistical summaries of your data and performing statistical tests and modeling. You’ll even learn how to create impressive data visualizations with R’s basic graphics tools and contributed packages, like ggplot2 and ggvis, as well as interactive 3D visualizations using the rgl package. Dozens of hands-on exercises (with downloadable solutions) take you from theory to practice, as you learn: –The fundamentals of programming in R, including how to write data frames, create functions, and use variables, statements, and loops –Statistical concepts like exploratory data analysis, probabilities, hypothesis tests, and regression modeling, and how to execute them in R –How to access R’s thousands of functions, libraries, and data sets –How to draw valid and useful conclusions from your data –How to create publication-quality graphics of your results Combining detailed explanations with real-world examples and exercises, this book will provide you with a solid understanding of both statistics and the depth of R’s functionality. Make The Book of R your doorway into the growing world of data analysis.
First Course in Statistical Inference
Author: Jonathan Gillard
Publisher:
ISBN: 9783030395629
Category : Inference
Languages : en
Pages : 164
Book Description
This book offers a modern and accessible introduction to Statistical Inference, the science of inferring key information from data. Aimed at beginning undergraduate students in mathematics, it presents the concepts underpinning frequentist statistical theory. Written in a conversational and informal style, this concise text concentrates on ideas and concepts, with key theorems stated and proved. Detailed worked examples are included and each chapter ends with a set of exercises, with full solutions given at the back of the book. Examples using R are provided throughout the book, with a brief guide to the software included. Topics covered in the book include: sampling distributions, properties of estimators, confidence intervals, hypothesis testing, ANOVA, and fitting a straight line to paired data. Based on the author's extensive teaching experience, the material of the book has been honed by student feedback for over a decade. Assuming only some familiarity with elementary probability, this textbook has been devised for a one semester first course in statistics.
Publisher:
ISBN: 9783030395629
Category : Inference
Languages : en
Pages : 164
Book Description
This book offers a modern and accessible introduction to Statistical Inference, the science of inferring key information from data. Aimed at beginning undergraduate students in mathematics, it presents the concepts underpinning frequentist statistical theory. Written in a conversational and informal style, this concise text concentrates on ideas and concepts, with key theorems stated and proved. Detailed worked examples are included and each chapter ends with a set of exercises, with full solutions given at the back of the book. Examples using R are provided throughout the book, with a brief guide to the software included. Topics covered in the book include: sampling distributions, properties of estimators, confidence intervals, hypothesis testing, ANOVA, and fitting a straight line to paired data. Based on the author's extensive teaching experience, the material of the book has been honed by student feedback for over a decade. Assuming only some familiarity with elementary probability, this textbook has been devised for a one semester first course in statistics.