Author: Rudolf J. Freund
Publisher: Elsevier
ISBN: 0080498221
Category : Mathematics
Languages : en
Pages : 694
Book Description
This broad text provides a complete overview of most standard statistical methods, including multiple regression, analysis of variance, experimental design, and sampling techniques. Assuming a background of only two years of high school algebra, this book teaches intelligent data analysis and covers the principles of good data collection. * Provides a complete discussion of analysis of data including estimation, diagnostics, and remedial actions * Examples contain graphical illustration for ease of interpretation * Intended for use with almost any statistical software * Examples are worked to a logical conclusion, including interpretation of results * A complete Instructor's Manual is available to adopters
Statistical Methods
Author: Rudolf J. Freund
Publisher: Elsevier
ISBN: 0080498221
Category : Mathematics
Languages : en
Pages : 694
Book Description
This broad text provides a complete overview of most standard statistical methods, including multiple regression, analysis of variance, experimental design, and sampling techniques. Assuming a background of only two years of high school algebra, this book teaches intelligent data analysis and covers the principles of good data collection. * Provides a complete discussion of analysis of data including estimation, diagnostics, and remedial actions * Examples contain graphical illustration for ease of interpretation * Intended for use with almost any statistical software * Examples are worked to a logical conclusion, including interpretation of results * A complete Instructor's Manual is available to adopters
Publisher: Elsevier
ISBN: 0080498221
Category : Mathematics
Languages : en
Pages : 694
Book Description
This broad text provides a complete overview of most standard statistical methods, including multiple regression, analysis of variance, experimental design, and sampling techniques. Assuming a background of only two years of high school algebra, this book teaches intelligent data analysis and covers the principles of good data collection. * Provides a complete discussion of analysis of data including estimation, diagnostics, and remedial actions * Examples contain graphical illustration for ease of interpretation * Intended for use with almost any statistical software * Examples are worked to a logical conclusion, including interpretation of results * A complete Instructor's Manual is available to adopters
Statistical Method from the Viewpoint of Quality Control
Author: Walter Andrew Shewhart
Publisher: Courier Corporation
ISBN: 9780486652320
Category : Mathematics
Languages : en
Pages : 218
Book Description
Important text offers lucid explanation of how to regulate variables and maintain control over statistics in order to achieve quality control over manufactured products, crops and data. Topics include statistical control, establishing limits of variability, measurements of physical properties and constants, and specification of accuracy and precision. First inexpensive paperback edition.
Publisher: Courier Corporation
ISBN: 9780486652320
Category : Mathematics
Languages : en
Pages : 218
Book Description
Important text offers lucid explanation of how to regulate variables and maintain control over statistics in order to achieve quality control over manufactured products, crops and data. Topics include statistical control, establishing limits of variability, measurements of physical properties and constants, and specification of accuracy and precision. First inexpensive paperback edition.
Statistical Methods in Customer Relationship Management
Author: V. Kumar
Publisher: John Wiley & Sons
ISBN: 1118349199
Category : Mathematics
Languages : en
Pages : 227
Book Description
Statistical Methods in Customer Relationship Management focuses on the quantitative and modeling aspects of customer management strategies that lead to future firm profitability, with emphasis on developing an understanding of Customer Relationship Management (CRM) models as the guiding concept for profitable customer management. To understand and explore the functioning of CRM models, this book traces the management strategies throughout a customer’s tenure with a firm. Furthermore, the book explores in detail CRM models for customer acquisition, customer retention, customer acquisition and retention, customer churn, and customer win back. Statistical Methods in Customer Relationship Management: Provides an overview of a CRM system, introducing key concepts and metrics needed to understand and implement these models. Focuses on five CRM models: customer acquisition, customer retention, customer churn, and customer win back with supporting case studies. Explores each model in detail, from investigating the need for CRM models to looking at the future of the models. Presents models and concepts that span across the introductory, advanced, and specialist levels. Academics and practitioners involved in the area of CRM as well as instructors of applied statistics and quantitative marketing courses will benefit from this book.
Publisher: John Wiley & Sons
ISBN: 1118349199
Category : Mathematics
Languages : en
Pages : 227
Book Description
Statistical Methods in Customer Relationship Management focuses on the quantitative and modeling aspects of customer management strategies that lead to future firm profitability, with emphasis on developing an understanding of Customer Relationship Management (CRM) models as the guiding concept for profitable customer management. To understand and explore the functioning of CRM models, this book traces the management strategies throughout a customer’s tenure with a firm. Furthermore, the book explores in detail CRM models for customer acquisition, customer retention, customer acquisition and retention, customer churn, and customer win back. Statistical Methods in Customer Relationship Management: Provides an overview of a CRM system, introducing key concepts and metrics needed to understand and implement these models. Focuses on five CRM models: customer acquisition, customer retention, customer churn, and customer win back with supporting case studies. Explores each model in detail, from investigating the need for CRM models to looking at the future of the models. Presents models and concepts that span across the introductory, advanced, and specialist levels. Academics and practitioners involved in the area of CRM as well as instructors of applied statistics and quantitative marketing courses will benefit from this book.
Principles & Methods of Statistical Analysis
Author: Jerome Frieman
Publisher: SAGE Publications
ISBN: 1483358607
Category : Social Science
Languages : en
Pages : 441
Book Description
This unique intermediate/advanced statistics text uses real research on antisocial behaviors, such as cyberbullying, stereotyping, prejudice, and discrimination, to help readers across the social and behavioral sciences understand the underlying theory behind statistical methods. By presenting examples and principles of statistics within the context of these timely issues, the text shows how the results of analyses can be used to answer research questions. New techniques for data analysis and a wide range of topics are covered, including how to deal with "messy data" and the importance of engaging in exploratory data analysis.
Publisher: SAGE Publications
ISBN: 1483358607
Category : Social Science
Languages : en
Pages : 441
Book Description
This unique intermediate/advanced statistics text uses real research on antisocial behaviors, such as cyberbullying, stereotyping, prejudice, and discrimination, to help readers across the social and behavioral sciences understand the underlying theory behind statistical methods. By presenting examples and principles of statistics within the context of these timely issues, the text shows how the results of analyses can be used to answer research questions. New techniques for data analysis and a wide range of topics are covered, including how to deal with "messy data" and the importance of engaging in exploratory data analysis.
The Statistical Analysis of Recurrent Events
Author: Richard J. Cook
Publisher: Springer Science & Business Media
ISBN: 0387698094
Category : Medical
Languages : en
Pages : 415
Book Description
This book presents models and statistical methods for the analysis of recurrent event data. The authors provide broad, detailed coverage of the major approaches to analysis, while emphasizing the modeling assumptions that they are based on. More general intensity-based models are also considered, as well as simpler models that focus on rate or mean functions. Parametric, nonparametric and semiparametric methodologies are all covered, with procedures for estimation, testing and model checking.
Publisher: Springer Science & Business Media
ISBN: 0387698094
Category : Medical
Languages : en
Pages : 415
Book Description
This book presents models and statistical methods for the analysis of recurrent event data. The authors provide broad, detailed coverage of the major approaches to analysis, while emphasizing the modeling assumptions that they are based on. More general intensity-based models are also considered, as well as simpler models that focus on rate or mean functions. Parametric, nonparametric and semiparametric methodologies are all covered, with procedures for estimation, testing and model checking.
Statistical Analysis Quick Reference Guidebook
Author: Alan C. Elliott
Publisher: SAGE
ISBN: 9781412925600
Category : Computers
Languages : en
Pages : 280
Book Description
A practical `cut to the chase′ handbook that quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision-making in a wide variety of disciplines. In this one-stop reference, the authors provide succinct guidelines for performing an analysis, avoiding pitfalls, interpreting results and reporting outcomes.
Publisher: SAGE
ISBN: 9781412925600
Category : Computers
Languages : en
Pages : 280
Book Description
A practical `cut to the chase′ handbook that quickly explains the when, where, and how of statistical data analysis as it is used for real-world decision-making in a wide variety of disciplines. In this one-stop reference, the authors provide succinct guidelines for performing an analysis, avoiding pitfalls, interpreting results and reporting outcomes.
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.
Basic Statistical Methods
Author: Norville Morgan Downie
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 312
Book Description
Publisher:
ISBN:
Category : Statistics
Languages : en
Pages : 312
Book Description
SAS for Data Analysis
Author: Mervyn G. Marasinghe
Publisher: Springer Science & Business Media
ISBN: 038777372X
Category : Mathematics
Languages : en
Pages : 562
Book Description
This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level s- tistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an - derstanding of basic concepts of statistical inference such as estimation and hypothesis testing. Understandably, adequate time is not available in a ?rst course in stat- tical methods to cover the use of a software system adequately in the amount of time available for instruction. The aim of this book is to teach how to use the SAS system for data analysis. The SAS language is introduced at a level of sophistication not found in most introductory SAS books. Important features such as SAS data step programming, pointers, and line-hold spe- ?ers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.
Publisher: Springer Science & Business Media
ISBN: 038777372X
Category : Mathematics
Languages : en
Pages : 562
Book Description
This book is intended for use as the textbook in a second course in applied statistics that covers topics in multiple regression and analysis of variance at an intermediate level. Generally, students enrolled in such courses are p- marily graduate majors or advanced undergraduate students from a variety of disciplines. These students typically have taken an introductory-level s- tistical methods course that requires the use a software system such as SAS for performing statistical analysis. Thus students are expected to have an - derstanding of basic concepts of statistical inference such as estimation and hypothesis testing. Understandably, adequate time is not available in a ?rst course in stat- tical methods to cover the use of a software system adequately in the amount of time available for instruction. The aim of this book is to teach how to use the SAS system for data analysis. The SAS language is introduced at a level of sophistication not found in most introductory SAS books. Important features such as SAS data step programming, pointers, and line-hold spe- ?ers are described in detail. The powerful graphics support available in SAS is emphasized throughout, and many worked SAS program examples contain graphic components.
Statistical Methods for Meta-Analysis
Author: Larry V. Hedges
Publisher: Academic Press
ISBN: 0080570658
Category : Mathematics
Languages : en
Pages : 392
Book Description
The main purpose of this book is to address the statistical issues for integrating independent studies. There exist a number of papers and books that discuss the mechanics of collecting, coding, and preparing data for a meta-analysis , and we do not deal with these. Because this book concerns methodology, the content necessarily is statistical, and at times mathematical. In order to make the material accessible to a wider audience, we have not provided proofs in the text. Where proofs are given, they are placed as commentary at the end of a chapter. These can be omitted at the discretion of the reader.Throughout the book we describe computational procedures whenever required. Many computations can be completed on a hand calculator, whereas some require the use of a standard statistical package such as SAS, SPSS, or BMD. Readers with experience using a statistical package or who conduct analyses such as multiple regression or analysis of variance should be able to carry out the analyses described with the aid of a statistical package.
Publisher: Academic Press
ISBN: 0080570658
Category : Mathematics
Languages : en
Pages : 392
Book Description
The main purpose of this book is to address the statistical issues for integrating independent studies. There exist a number of papers and books that discuss the mechanics of collecting, coding, and preparing data for a meta-analysis , and we do not deal with these. Because this book concerns methodology, the content necessarily is statistical, and at times mathematical. In order to make the material accessible to a wider audience, we have not provided proofs in the text. Where proofs are given, they are placed as commentary at the end of a chapter. These can be omitted at the discretion of the reader.Throughout the book we describe computational procedures whenever required. Many computations can be completed on a hand calculator, whereas some require the use of a standard statistical package such as SAS, SPSS, or BMD. Readers with experience using a statistical package or who conduct analyses such as multiple regression or analysis of variance should be able to carry out the analyses described with the aid of a statistical package.