Author: Ira H. Bernstein
Publisher: SAGE Publications, Incorporated
ISBN:
Category : Computers
Languages : en
Pages : 464
Book Description
A textbook for a course teaching students of behavioral sciences how to analyze data using some of the software that has become available for personal computers. Bernstein and Rowe, presumably teachers somewhere, have revived demonstrations as an approach to teaching statistics. They assume students have at least some familiarity with the language and various topics taught in graduate statistics, multivariate analysis, and psychometric theory courses, but not to be experts in any of those fields. c. Book News Inc.
Statistical Data Analysis Using Your Personal Computer
Author: Ira H. Bernstein
Publisher: SAGE Publications, Incorporated
ISBN:
Category : Computers
Languages : en
Pages : 464
Book Description
A textbook for a course teaching students of behavioral sciences how to analyze data using some of the software that has become available for personal computers. Bernstein and Rowe, presumably teachers somewhere, have revived demonstrations as an approach to teaching statistics. They assume students have at least some familiarity with the language and various topics taught in graduate statistics, multivariate analysis, and psychometric theory courses, but not to be experts in any of those fields. c. Book News Inc.
Publisher: SAGE Publications, Incorporated
ISBN:
Category : Computers
Languages : en
Pages : 464
Book Description
A textbook for a course teaching students of behavioral sciences how to analyze data using some of the software that has become available for personal computers. Bernstein and Rowe, presumably teachers somewhere, have revived demonstrations as an approach to teaching statistics. They assume students have at least some familiarity with the language and various topics taught in graduate statistics, multivariate analysis, and psychometric theory courses, but not to be experts in any of those fields. c. Book News Inc.
Introduction to Statistics and Data Analysis
Author: Christian Heumann
Publisher: Springer Nature
ISBN: 3031118332
Category : Mathematics
Languages : en
Pages : 584
Book Description
Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.
Publisher: Springer Nature
ISBN: 3031118332
Category : Mathematics
Languages : en
Pages : 584
Book Description
Now in its second edition, this introductory statistics textbook conveys the essential concepts and tools needed to develop and nurture statistical thinking. It presents descriptive, inductive and explorative statistical methods and guides the reader through the process of quantitative data analysis. This revised and extended edition features new chapters on logistic regression, simple random sampling, including bootstrapping, and causal inference. The text is primarily intended for undergraduate students in disciplines such as business administration, the social sciences, medicine, politics, and macroeconomics. It features a wealth of examples, exercises and solutions with computer code in the statistical programming language R, as well as supplementary material that will enable the reader to quickly adapt the methods to their own applications.
Statistical Data Analysis
Author: Milan Meloun
Publisher: Woodhead Publishing Limited
ISBN: 9780857091093
Category : Chemical engineering
Languages : en
Pages : 0
Book Description
Over the past decade, computer supported data analysis by statistical methods has been one of the fastest growth areas in chemometrics, biometrics and other related branches of natural, technical and social sciences. This has been strongly supported by the development of exploratory data analysis, testing assumptions about data, model and statistical methods and computer intensive techniques. This book presents a combination of individual topics with solved problems and a collection of experimental tasks. Methods suitable for extreme or small and large datasets are described. Presents a combination of individual topics in one complete volume featuring statistical analysis of univariate and multivariate data Interspersed throughout with solved problems and experimental tasks suitable for extreme or small and large datasets Features the interpretation of results based on the comprehensive information about data behaviour and validity of used assumptions
Publisher: Woodhead Publishing Limited
ISBN: 9780857091093
Category : Chemical engineering
Languages : en
Pages : 0
Book Description
Over the past decade, computer supported data analysis by statistical methods has been one of the fastest growth areas in chemometrics, biometrics and other related branches of natural, technical and social sciences. This has been strongly supported by the development of exploratory data analysis, testing assumptions about data, model and statistical methods and computer intensive techniques. This book presents a combination of individual topics with solved problems and a collection of experimental tasks. Methods suitable for extreme or small and large datasets are described. Presents a combination of individual topics in one complete volume featuring statistical analysis of univariate and multivariate data Interspersed throughout with solved problems and experimental tasks suitable for extreme or small and large datasets Features the interpretation of results based on the comprehensive information about data behaviour and validity of used assumptions
Statistical Analysis of Network Data
Author: Eric D. Kolaczyk
Publisher: Springer Science & Business Media
ISBN: 0387881468
Category : Computers
Languages : en
Pages : 397
Book Description
In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.
Publisher: Springer Science & Business Media
ISBN: 0387881468
Category : Computers
Languages : en
Pages : 397
Book Description
In recent years there has been an explosion of network data – that is, measu- ments that are either of or from a system conceptualized as a network – from se- ingly all corners of science. The combination of an increasingly pervasive interest in scienti c analysis at a systems level and the ever-growing capabilities for hi- throughput data collection in various elds has fueled this trend. Researchers from biology and bioinformatics to physics, from computer science to the information sciences, and from economics to sociology are more and more engaged in the c- lection and statistical analysis of data from a network-centric perspective. Accordingly, the contributions to statistical methods and modeling in this area have come from a similarly broad spectrum of areas, often independently of each other. Many books already have been written addressing network data and network problems in speci c individual disciplines. However, there is at present no single book that provides a modern treatment of a core body of knowledge for statistical analysis of network data that cuts across the various disciplines and is organized rather according to a statistical taxonomy of tasks and techniques. This book seeks to ll that gap and, as such, it aims to contribute to a growing trend in recent years to facilitate the exchange of knowledge across the pre-existing boundaries between those disciplines that play a role in what is coming to be called ‘network science.
Statistical Data Analysis
Author: Glen Cowan
Publisher: Oxford University Press
ISBN: 0198501560
Category : Mathematics
Languages : en
Pages : 218
Book Description
This book is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences. It is primarily addressed at students and professionals who need to draw quantitative conclusions from experimental data. Although most of the examples are takenfrom particle physics, the material is presented in a sufficiently general way as to be useful to people from most branches of the physical sciences. The first part of the book describes the basic tools of data analysis: concepts of probability and random variables, Monte Carlo techniques,statistical tests, and methods of parameter estimation. The last three chapters are somewhat more specialized than those preceding, covering interval estimation, characteristic functions, and the problem of correcting distributions for the effects of measurement errors (unfolding).
Publisher: Oxford University Press
ISBN: 0198501560
Category : Mathematics
Languages : en
Pages : 218
Book Description
This book is a guide to the practical application of statistics in data analysis as typically encountered in the physical sciences. It is primarily addressed at students and professionals who need to draw quantitative conclusions from experimental data. Although most of the examples are takenfrom particle physics, the material is presented in a sufficiently general way as to be useful to people from most branches of the physical sciences. The first part of the book describes the basic tools of data analysis: concepts of probability and random variables, Monte Carlo techniques,statistical tests, and methods of parameter estimation. The last three chapters are somewhat more specialized than those preceding, covering interval estimation, characteristic functions, and the problem of correcting distributions for the effects of measurement errors (unfolding).
Statistical Techniques for Data Analysis
Author: John K. Taylor
Publisher: CRC Press
ISBN: 0203492390
Category : Mathematics
Languages : en
Pages : 294
Book Description
Since the first edition of this book appeared, computers have come to the aid of modern experimenters and data analysts, bringing with them data analysis techniques that were once beyond the calculational reach of even professional statisticians. Today, scientists in every field have access to the techniques and technology they need to analyze stat
Publisher: CRC Press
ISBN: 0203492390
Category : Mathematics
Languages : en
Pages : 294
Book Description
Since the first edition of this book appeared, computers have come to the aid of modern experimenters and data analysts, bringing with them data analysis techniques that were once beyond the calculational reach of even professional statisticians. Today, scientists in every field have access to the techniques and technology they need to analyze stat
Data Analysis Using SPSS for Windows Versions 8 - 10
Author: Jeremy J Foster
Publisher: SAGE
ISBN: 9780761969273
Category : Social Science
Languages : en
Pages : 276
Book Description
A new edition of this best-selling introductory book to cover the latest SPSS versions 8.0 - 10.0 This book is designed to teach beginners how to use SPSS for Windows, the most widely used computer package for analysing quantitative data. Written in a clear, readable and non-technical style the author explains the basics of SPSS including the input of data, data manipulation, descriptive analyses and inferential techniques, including; - creating using and merging data files - creating and printing graphs and charts - parametric tests including t-tests, ANOVA, GLM - correlation, regression and factor analysis - non parametric tests and chi square reliability - obtaining neat print outs and tables - includes a CD-Rom containing example data files, syntax files, output files and Excel spreadsheets.
Publisher: SAGE
ISBN: 9780761969273
Category : Social Science
Languages : en
Pages : 276
Book Description
A new edition of this best-selling introductory book to cover the latest SPSS versions 8.0 - 10.0 This book is designed to teach beginners how to use SPSS for Windows, the most widely used computer package for analysing quantitative data. Written in a clear, readable and non-technical style the author explains the basics of SPSS including the input of data, data manipulation, descriptive analyses and inferential techniques, including; - creating using and merging data files - creating and printing graphs and charts - parametric tests including t-tests, ANOVA, GLM - correlation, regression and factor analysis - non parametric tests and chi square reliability - obtaining neat print outs and tables - includes a CD-Rom containing example data files, syntax files, output files and Excel spreadsheets.
Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities
Author: Segall, Richard S.
Publisher: IGI Global
ISBN: 1799827704
Category : Computers
Languages : en
Pages : 237
Book Description
With the development of computing technologies in today’s modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.
Publisher: IGI Global
ISBN: 1799827704
Category : Computers
Languages : en
Pages : 237
Book Description
With the development of computing technologies in today’s modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.
InfoWorld
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 68
Book Description
InfoWorld is targeted to Senior IT professionals. Content is segmented into Channels and Topic Centers. InfoWorld also celebrates people, companies, and projects.
Publisher:
ISBN:
Category :
Languages : en
Pages : 68
Book Description
InfoWorld is targeted to Senior IT professionals. Content is segmented into Channels and Topic Centers. InfoWorld also celebrates people, companies, and projects.
InfoWorld
Author:
Publisher:
ISBN:
Category :
Languages : en
Pages : 112
Book Description
InfoWorld is targeted to Senior IT professionals. Content is segmented into Channels and Topic Centers. InfoWorld also celebrates people, companies, and projects.
Publisher:
ISBN:
Category :
Languages : en
Pages : 112
Book Description
InfoWorld is targeted to Senior IT professionals. Content is segmented into Channels and Topic Centers. InfoWorld also celebrates people, companies, and projects.