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25 produkter

Permutation, Parametric, and Bootstrap Tests of Hypotheses
AvPhillip I. Good
Inbunden, Engelska, 2004
2 215 kr
Skickas inom 10-15 vardagar
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthetrainingofreal-worldstatisticiansand biostatisticians. In previous editions of this text, my rhetoric was somewhat tentative. I was saying, in e?ect, “Gee guys, permutation methods provide a practical real-world alternative to asymptotic parametric approximations. Why not give them a try?” But today, the theory, the software, and the hardware have come together. Distribution-free permutation procedures are the primary method for testing hypotheses. Parametric procedures and the bootstrap are to be reserved for the few situations in which they may be applicable. Four factors have forced this change: 1. Desire by workers in applied ?elds to use the most powerful statistic for their applications. Such workers may not be aware of the fundamental lemma of Neyman and Pearson, but they know that the statistic they wanttouse—acomplexscoreoraratioofscores,doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not approximations. 3. A growing recognition that most real-world data are drawn from mixtures of populations. 4. A growing recognition that missing data is inevitable, balanced designs the exception. Thus, it seems natural that the theory of testing hypothesis and the more general decision theory in which it is embedded should be introduced via the permutation tests. On the other hand, certain relatively robust param- ric tests such as Student’s t continue to play an essential role in statistical practice.
Permutation, Parametric, and Bootstrap Tests of Hypotheses
AvPhillip I. Good
E-bok
PDF, Engelska, 2005
2 769 kr
Läs direkt efter köp
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthetrainingofreal-worldstatisticiansand biostatisticians. In previous editions of this text, my rhetoric was somewhat tentative. I was saying, in e?ect, “Gee guys, permutation methods provide a practical real-world alternative to asymptotic parametric approximations. Why not give them a try?” But today, the theory, the software, and the hardware have come together. Distribution-free permutation procedures are the primary method for testing hypotheses. Parametric procedures and the bootstrap are to be reserved for the few situations in which they may be applicable. Four factors have forced this change: 1. Desire by workers in applied ?elds to use the most powerful statistic for their applications. Such workers may not be aware of the fundamental lemma of Neyman and Pearson, but they know that the statistic they wanttouse—acomplexscoreoraratioofscores,doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not approximations. 3. A growing recognition that most real-world data are drawn from mixtures of populations. 4. A growing recognition that missing data is inevitable, balanced designs the exception. Thus, it seems natural that the theory of testing hypothesis and the more general decision theory in which it is embedded should be introduced via the permutation tests. On the other hand, certain relatively robust param- ric tests such as Student’s t continue to play an essential role in statistical practice.
Common Errors in Statistics (and How to Avoid Them)
AvJames W. Hardin,Phillip I. Good
E-bok
PDF, Engelska, 2009
725 kr
Läs direkt efter köp
Praise for the Second Edition
"All statistics students and teachers will find in this book a friendly and intelligentguide to . . . applied statistics in practice." —Journal of Applied Statistics

". . . a very engaging and valuable book for all who use statistics in any setting." —CHOICE

". . . a concise guide to the basics of statistics, replete with examples . . . a valuablereference for more advanced statisticians as well." —MAA Reviews

Now in its Third Edition, the highly readable Common Errors in Statistics (and How to Avoid Them) continues to serve as a thorough and straightforward discussion of basic statistical methods, presentations, approaches, and modeling techniques. Further enriched with new examples and counterexamples from the latest research as well as added coverage of relevant topics, this new edition of the benchmark book addresses popular mistakes often made in data collection and provides an indispensable guide to accurate statistical analysis and reporting. The authors'' emphasis on careful practice, combined with a focus on the development of solutions, reveals the true value of statistics when applied correctly in any area of research.

The Third Edition has been considerably expanded and revised to include:
A new chapter on data quality assessment
A new chapter on correlated data

An expanded chapter on data analysis covering categorical and ordinal data, continuous measurements, and time-to-event data, including sections on factorial and crossover designs

Revamped exercises with a stronger emphasis on solutions

An extended chapter on report preparation

New sections on factor analysis as well as Poisson and negative binomial regression

Providing valuable, up-to-date information in the same user-friendly format as its predecessor, Common Errors in Statistics (and How to Avoid Them), Third Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences.
Analyzing the Large Number of Variables in Biomedical and Satellite Imagery
AvPhillip I. Good
Häftad, Engelska, 2011
993 kr
Skickas inom 5-8 vardagar
This book grew out of an online interactive offered through statcourse.com, and it soon became apparent to the author that the course was too limited in terms of time and length in light of the broad backgrounds of the enrolled students. The statisticians who took the course needed to be brought up to speed both on the biological context as well as on the specialized statistical methods needed to handle large arrays. Biologists and physicians, even though fully knowledgeable concerning the procedures used to generate microaarrays, EEGs, or MRIs, needed a full introduction to the resampling methods—the bootstrap, decision trees, and permutation tests, before the specialized methods applicable to large arrays could be introduced. As the intended audience for this book consists both of statisticians and of medical and biological research workers as well as all those research workers who make use of satellite imagery including agronomists and meteorologists, the book provides a step-by-step approach to not only the specialized methods needed to analyze the data from microarrays and images, but also to the resampling methods, step-down multi-comparison procedures, multivariate analysis, as well as data collection and pre-processing. While many alternate techniques for analysis have been introduced in the past decade, the author has selected only those techniques for which software is available along with a list of the available links from which the software may be purchased or downloaded without charge. Topical coverage includes: very large arrays; permutation tests; applying permutation tests; gathering and preparing data for analysis; multiple tests; bootstrap; applying the bootstrap; classification methods; decision trees; and applying decision trees.
Analyzing the Large Number of Variables in Biomedical and Satellite Imagery
AvPhillip I. Good
E-bok
PDF, Engelska, 2011
1 116 kr
Läs direkt efter köp
This book grew out of an online interactive offered through statcourse.com, and it soon became apparent to the author that the course was too limited in terms of time and length in light of the broad backgrounds of the enrolled students. The statisticians who took the course needed to be brought up to speed both on the biological context as well as on the specialized statistical methods needed to handle large arrays. Biologists and physicians, even though fully knowledgeable concerning the procedures used to generate microaarrays, EEGs, or MRIs, needed a full introduction to the resampling methods—the bootstrap, decision trees, and permutation tests, before the specialized methods applicable to large arrays could be introduced. As the intended audience for this book consists both of statisticians and of medical and biological research workers as well as all those research workers who make use of satellite imagery including agronomists and meteorologists, the book provides a step-by-step approach to not only the specialized methods needed to analyze the data from microarrays and images, but also to the resampling methods, step-down multi-comparison procedures, multivariate analysis, as well as data collection and pre-processing. While many alternate techniques for analysis have been introduced in the past decade, the author has selected only those techniques for which software is available along with a list of the available links from which the software may be purchased or downloaded without charge. Topical coverage includes: very large arrays; permutation tests; applying permutation tests; gathering and preparing data for analysis; multiple tests; bootstrap; applying the bootstrap; classification methods; decision trees; and applying decision trees.
Introduction to Statistics Through Resampling Methods and Microsoft Office Excel
AvPhillip I. Good
Häftad, Engelska, 2005
1 361 kr
Skickas inom 5-8 vardagar
Learn statistical methods quickly and easily with the discovery method With its emphasis on the discovery method, this publication encourages readers to discover solutions on their own rather than simply copy answers or apply a formula by rote. Readers quickly master and learn to apply statistical methods, such as bootstrap, decision trees, t-test, and permutations to better characterize, report, test, and classify their research findings. In addition to traditional methods, specialized methods are covered, allowing readers to select and apply the most effective method for their research, including:* Tests and estimation procedures for one, two, and multiple samples* Model building* Multivariate analysis* Complex experimental design Throughout the text, Microsoft Office Excel(r) is used to illustrate new concepts and assist readers in completing exercises. An Excel Primer is included as an Appendix for readers who need to learn or brush up on their Excel skills. Written in an informal, highly accessible style, this text is an excellent guide to descriptive statistics, estimation, testing hypotheses, and model building. All the pedagogical tools needed to facilitate quick learning are provided:* More than 100 exercises scattered throughout the text stimulate readers' thinking and actively engage them in applying their newfound skills* Companion FTP site provides access to all data sets discussed in the text* An Instructor's Manual is available upon request from the publisher* Dozens of thought-provoking questions in the final chapter assist readers in applying statistics to solve real-life problems* Helpful appendices include an index to Excel and Excel add-in functions This text serves as an excellent introduction to statistics for students in all disciplines. The accessible style and focus on real-life problem solving are perfectly suited to both students and practitioners.
Introduction to Statistics Through Resampling Methods and Microsoft Office Excel
AvPhillip I. Good
E-bok
PDF, Engelska, 2005
1 562 kr
Läs direkt efter köp
Learn statistical methods quickly and easily with the discovery method With its emphasis on the discovery method, this publication encourages readers to discover solutions on their own rather than simply copy answers or apply a formula by rote. Readers quickly master and learn to apply statistical methods, such as bootstrap, decision trees, t-test, and permutations to better characterize, report, test, and classify their research findings. In addition to traditional methods, specialized methods are covered, allowing readers to select and apply the most effective method for their research, including: * Tests and estimation procedures for one, two, and multiple samples * Model building * Multivariate analysis * Complex experimental design Throughout the text, Microsoft Office Excel(r) is used to illustrate new concepts and assist readers in completing exercises. An Excel Primer is included as an Appendix for readers who need to learn or brush up on their Excel skills. Written in an informal, highly accessible style, this text is an excellent guide to descriptive statistics, estimation, testing hypotheses, and model building. All the pedagogical tools needed to facilitate quick learning are provided: * More than 100 exercises scattered throughout the text stimulate readers'' thinking and actively engage them in applying their newfound skills * Companion FTP site provides access to all data sets discussed in the text * An Instructor''s Manual is available upon request from the publisher * Dozens of thought-provoking questions in the final chapter assist readers in applying statistics to solve real-life problems * Helpful appendices include an index to Excel and Excel add-in functions This text serves as an excellent introduction to statistics for students in all disciplines. The accessible style and focus on real-life problem solving are perfectly suited to both students and practitioners.
Manager's Guide to the Design and Conduct of Clinical Trials
AvPhillip I. Good
Inbunden, Engelska, 2006
1 826 kr
Skickas inom 3-6 vardagar
This newly updated edition of the benchmark guide to computer-assisted clinical trials provides a comprehensive primer for prospective managers. It covers every critical issue of the design and conduct of clinical trials, including study design, organization, regulatory agency liaison, data collection and analysis, as well as recruitment, software, monitoring, and reporting. Keeping the same user-friendly format as the original, this Second Edition features new examples and the latest developments in regulatory guidelines, such as e-submission procedures and computerized direct data acquisition. The new edition also reflects the increasing globalization of clinical trial activities, and includes new information about international standards and procedures, including the Common Technical Document and CDISC standards. This step-by-step guide is supported by handy checklists and extracts from submitted protocols. Experienced author and consultant Phillip Good incorporateshumorous yet instructive anecdotes to illustrate common pitfalls. Based on the proven industrial formula of planning, implementing, and finally performing essential checks, the book's three sections-"Plan," "Do," and "Check"-includethe following material:* Should the trials be conducted?* Put it in the computer and keep it there* Staffing for success* Designing trials and determining sample size* Budgeting* Recruiting and retaining patients and physicians* Data management* Monitoring the trials* Data analysis* After action review* Exception handling Executive and managerial professionals involved in the design and analysis of clinical experiments, along with clinical research associates, biostatisticians, and students in public health will find A Manager's Guide an indispensable resource. Praise for the First Edition: ". . . readable, informative and at times witty . . . never stops being concise and well written . . . a book worth a read . . ."-Statistics in Medicine "The book is very prescriptive and full of lists and tables with which to guide managers in making effective decisions in using computer-assisted clinical trials in pharmaceutical studies." -Technometrics "This book is must-have reading for anyone in the business . . ."-Clinical Chemistry
Manager's Guide to the Design and Conduct of Clinical Trials
AvPhillip I. Good
E-bok
PDF, Engelska, 2006
1 806 kr
Läs direkt efter köp
This newly updated edition of the benchmark guide to computer-assisted clinical trials provides a comprehensive primer for prospective managers. It covers every critical issue of the design and conduct of clinical trials, including study design, organization, regulatory agency liaison, data collection and analysis, as well as recruitment, software, monitoring, and reporting. Keeping the same user-friendly format as the original, this Second Edition features new examples and the latest developments in regulatory guidelines, such as e-submission procedures and computerized direct data acquisition. The new edition also reflects the increasing globalization of clinical trial activities, and includes new information about international standards and procedures, including the Common Technical Document and CDISC standards. This step-by-step guide is supported by handy checklists and extracts from submitted protocols. Experienced author and consultant Phillip Good incorporateshumorous yet instructive anecdotes to illustrate common pitfalls. Based on the proven industrial formula of planning, implementing, and finally performing essential checks, the book''s three sections-"Plan," "Do," and "Check"-includethe following material: * Should the trials be conducted? * Put it in the computer and keep it there * Staffing for success * Designing trials and determining sample size * Budgeting * Recruiting and retaining patients and physicians * Data management * Monitoring the trials * Data analysis * After action review * Exception handling Executive and managerial professionals involved in the design and analysis of clinical experiments, along with clinical research associates, biostatisticians, and students in public health will find A Manager''s Guide an indispensable resource. Praise for the First Edition: ". . . readable, informative and at times witty . . . never stops being concise and well written . . . a book worth a read . . ." -Statistics in Medicine "The book is very prescriptive and full of lists and tables with which to guide managers in making effective decisions in using computer-assisted clinical trials in pharmaceutical studies." -Technometrics "This book is must-have reading for anyone in the business . . ." -Clinical Chemistry
Common Errors in Statistics (and How to Avoid Them)
AvJames W. Hardin,Phillip I. Good
E-bok
PDF, Engelska, 2006
1 100 kr
Läs direkt efter köp
Praise for the First Edition of Common Errors in Statistics " . . . let me recommend Common Errors to all those who interact with statistics, whatever their level of statistical understanding . . . " --Stats 40 " . . . written . . . for the people who define good practice rather than seek to emulate it." --Journal of Biopharmaceutical Statistics " . . . highly informative, enjoyable to read, and of potential use to a broad audience. It is a book that should be on the reference shelf of many statisticians and researchers." --The American Statistician " . . . I found this book the most easily readable statistics book ever. The credit for this certainly goes to Phillip Good." --E-STREAMS A tried-and-true guide to the proper application of statistics Now in a second edition, the highly readable Common Errors in Statistics (and How to Avoid Them) lays a mathematically rigorous and readily accessible foundation for understanding statistical procedures, problems, and solutions. This handy field guide analyzes common mistakes, debunks popular myths, and helps readers to choose the best and most effective statistical technique for each of their tasks. Written for both the newly minted academic and the professional who uses statistics in their work, the book covers creating a research plan, formulating a hypothesis, specifying sample size, checking assumptions, interpreting p-values and confidence intervals, building a model, data mining, Bayes'' Theorem, the bootstrap, and many other topics. The Second Edition has been extensively revised to include: * Additional charts and graphs * Two new chapters, Interpreting Reports and Which Regression Method? * New sections on practical versus statistical significance and nonuniqueness in multivariate regression * Added material from the authors'' online courses at statistics.com * New material on unbalanced designs, report interpretation, and alternative modeling methods With a final emphasis on both finding solutions and the great value of statistics when applied in the proper context, this book is eminently useful to students and professionals in the fields of research, industry, medicine, and government.
Resampling Methods
A Practical Guide to Data Analysis
AvPhillip I. Good
Inbunden, Engelska, 2005
1 000 kr
Skickas inom 10-15 vardagar
"…the author has packaged an excellent and modern set of topics around the development and use of quantitative models.... If you need to learn about resampling, this book would be a good place to start." Technometrics (Review of the Second Edition)This thoroughly revised and expanded third edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. Only requiring minimal mathematics beyond algebra, the book provides a table-free introduction to data analysis utilizing numerous exercises, practical data sets, and freely available statistical shareware.Topics and Features- Practical presentation covers both the bootstrap and permutations along with the program code necessary to put them to work.- Includes a systematic guide to selecting the correct procedure for a particular application. - Detailed coverage of classification, estimation, experimental design, hypothesis testing, and modeling. - Suitable for both classroom use and individual self-study. New to the Third Edition - Procedures are grouped by application; a prefatory chapter guides readers to the appropriate reading matter.- Program listings and screen shots now accompany each resampling procedure. - To simplify programming, code for readers to download and apply is posted at http://www.springeronline.com/0-8176-4386-9. - Notation has been simplified and, where possible, eliminated. - A glossary and answers to selected exercises are included. With its accessible style and intuitive topic development, the book is an excellent basic resource for the power, simplicity, and versatility of resampling methods. It is an essential resource for statisticians, biostatisticians, statistical consultants, students, and research professionals in the biological, physical, and social sciences, engineering, and technology.
Resampling Methods
A Practical Guide to Data Analysis
AvPhillip I. Good
E-bok
PDF, Engelska, 2006
1 255 kr
Läs direkt efter köp
"…the author has packaged an excellent and modern set of topics around the development and use of quantitative models.... If you need to learn about resampling, this book would be a good place to start." Technometrics (Review of the Second Edition)
This thoroughly revised and expanded third edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. Only requiring minimal mathematics beyond algebra, the book provides a table-free introduction to data analysis utilizing numerous exercises, practical data sets, and freely available statistical shareware.
Topics and Features
- Practical presentation covers both the bootstrap and permutations along with the program code necessary to put them to work.
- Includes a systematic guide to selecting the correct procedure for a particular application.
- Detailed coverage of classification, estimation, experimental design, hypothesis testing, and modeling.
- Suitable for both classroom use and individual self-study.
New to the Third Edition
- Procedures are grouped by application; a prefatory chapter guides readers to the appropriate reading matter.
- Program listings and screen shots now accompany each resampling procedure.
- To simplify programming, code for readers to download and apply is posted at http://www.springeronline.com/0-8176-4386-9.
- Notation has been simplified and, where possible, eliminated.
- A glossary and answers to selected exercises are included.
With its accessible style and intuitive topic development, the book is an excellent basic resource for the power, simplicity, and versatility of resampling methods. It is an essential resource for statisticians, biostatisticians, statistical consultants, students, and research professionals in the biological, physical, and social sciences, engineering, and technology.
Analyzing the Large Number of Variables in Biomedical and Satellite Imagery
AvPhillip I. Good
E-bok
Engelska, 2011
1 104 kr
Läs direkt efter köp
This book grew out of an online interactive offered through statcourse.com, and it soon became apparent to the author that the course was too limited in terms of time and length in light of the broad backgrounds of the enrolled students. The statisticians who took the course needed to be brought up to speed both on the biological context as well as on the specialized statistical methods needed to handle large arrays. Biologists and physicians, even though fully knowledgeable concerning the procedures used to generate microaarrays, EEGs, or MRIs, needed a full introduction to the resampling methods—the bootstrap, decision trees, and permutation tests, before the specialized methods applicable to large arrays could be introduced. As the intended audience for this book consists both of statisticians and of medical and biological research workers as well as all those research workers who make use of satellite imagery including agronomists and meteorologists, the book provides a step-by-step approach to not only the specialized methods needed to analyze the data from microarrays and images, but also to the resampling methods, step-down multi-comparison procedures, multivariate analysis, as well as data collection and pre-processing. While many alternate techniques for analysis have been introduced in the past decade, the author has selected only those techniques for which software is available along with a list of the available links from which the software may be purchased or downloaded without charge. Topical coverage includes: very large arrays; permutation tests; applying permutation tests; gathering and preparing data for analysis; multiple tests; bootstrap; applying the bootstrap; classification methods; decision trees; and applying decision trees.
Common Errors in Statistics (and How to Avoid Them)
AvJames W. Hardin,Phillip I. Good
E-bok
Engelska, 2011
725 kr
Läs direkt efter köp
Praise for the Second Edition
"All statistics students and teachers will find in this book a friendly and intelligentguide to . . . applied statistics in practice." —Journal of Applied Statistics

". . . a very engaging and valuable book for all who use statistics in any setting." —CHOICE

". . . a concise guide to the basics of statistics, replete with examples . . . a valuablereference for more advanced statisticians as well." —MAA Reviews

Now in its Third Edition, the highly readable Common Errors in Statistics (and How to Avoid Them) continues to serve as a thorough and straightforward discussion of basic statistical methods, presentations, approaches, and modeling techniques. Further enriched with new examples and counterexamples from the latest research as well as added coverage of relevant topics, this new edition of the benchmark book addresses popular mistakes often made in data collection and provides an indispensable guide to accurate statistical analysis and reporting. The authors'' emphasis on careful practice, combined with a focus on the development of solutions, reveals the true value of statistics when applied correctly in any area of research.

The Third Edition has been considerably expanded and revised to include:
A new chapter on data quality assessment
A new chapter on correlated data

An expanded chapter on data analysis covering categorical and ordinal data, continuous measurements, and time-to-event data, including sections on factorial and crossover designs

Revamped exercises with a stronger emphasis on solutions

An extended chapter on report preparation

New sections on factor analysis as well as Poisson and negative binomial regression

Providing valuable, up-to-date information in the same user-friendly format as its predecessor, Common Errors in Statistics (and How to Avoid Them), Third Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences.
Common Errors in Statistics (and How to Avoid Them)
AvPhillip I. Good,James W. Hardin
Häftad, Engelska, 2012
745 kr
Skickas inom 5-8 vardagar
Praise for Common Errors in Statistics (and How to Avoid Them)"A very engaging and valuable book for all who use statistics in any setting."CHOICE"Addresses popular mistakes often made in data collection and provides an indispensable guide to accurate statistical analysis and reporting. The authors' emphasis on careful practice, combined with a focus on the development of solutions, reveals the true value of statistics when applied correctly in any area of research."MAA ReviewsCommon Errors in Statistics (and How to Avoid Them), Fourth Edition provides a mathematically rigorous, yet readily accessible foundation in statistics for experienced readers as well as students learning to design and complete experiments, surveys, and clinical trials.Providing a consistent level of coherency throughout, the highly readable Fourth Edition focuses on debunking popular myths, analyzing common mistakes, and instructing readers on how to choose the appropriate statistical technique to address their specific task. The authors begin with an introduction to the main sources of error and provide techniques for avoiding them. Subsequent chapters outline key methods and practices for accurate analysis, reporting, and model building. The Fourth Edition features newly added topics, including: Baseline dataDetecting fraudLinear regression versus linear behaviorCase control studiesMinimum reporting requirementsNon-random samplesThe book concludes with a glossary that outlines key terms, and an extensive bibliography with several hundred citations directing readers to resources for further study.Presented in an easy-to-follow style, Common Errors in Statistics, Fourth Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences.
Common Errors in Statistics (and How to Avoid Them)
AvJames W. Hardin,Phillip I. Good
E-bok
Engelska, 2012
852 kr
Läs direkt efter köp
Praise for Common Errors in Statistics (and How to Avoid Them)

"A very engaging and valuable book for all who use statistics in any setting." CHOICE

"Addresses popular mistakes often made in data collection and provides an indispensable guide to accurate statistical analysis and reporting. The authors'' emphasis on careful practice, combined with a focus on the development of solutions, reveals the true value of statistics when applied correctly in any area of research." MAA Reviews

Common Errors in Statistics (and How to Avoid Them), Fourth Edition provides a mathematically rigorous, yet readily accessible foundation in statistics for experienced readers as well as students learning to design and complete experiments, surveys, and clinical trials.

Providing a consistent level of coherency throughout, the highly readable Fourth Edition focuses on debunking popular myths, analyzing common mistakes, and instructing readers on how to choose the appropriate statistical technique to address their specific task. The authors begin with an introduction to the main sources of error and provide techniques for avoiding them. Subsequent chapters outline key methods and practices for accurate analysis, reporting, and model building. The Fourth Edition features newly added topics, including:
Baseline data Detecting fraud Linear regression versus linear behavior Case control studies Minimum reporting requirements Non-random samples
The book concludes with a glossary that outlines key terms, and an extensive bibliography with several hundred citations directing readers to resources for further study.

Presented in an easy-to-follow style, Common Errors in Statistics, Fourth Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences.
Common Errors in Statistics (and How to Avoid Them)
AvJames W. Hardin,Phillip I. Good
E-bok
PDF, Engelska, 2012
852 kr
Läs direkt efter köp
Praise for Common Errors in Statistics (and How to Avoid Them)

"A very engaging and valuable book for all who use statistics in any setting." CHOICE

"Addresses popular mistakes often made in data collection and provides an indispensable guide to accurate statistical analysis and reporting. The authors'' emphasis on careful practice, combined with a focus on the development of solutions, reveals the true value of statistics when applied correctly in any area of research." MAA Reviews

Common Errors in Statistics (and How to Avoid Them), Fourth Edition provides a mathematically rigorous, yet readily accessible foundation in statistics for experienced readers as well as students learning to design and complete experiments, surveys, and clinical trials.

Providing a consistent level of coherency throughout, the highly readable Fourth Edition focuses on debunking popular myths, analyzing common mistakes, and instructing readers on how to choose the appropriate statistical technique to address their specific task. The authors begin with an introduction to the main sources of error and provide techniques for avoiding them. Subsequent chapters outline key methods and practices for accurate analysis, reporting, and model building. The Fourth Edition features newly added topics, including:
Baseline data Detecting fraud Linear regression versus linear behavior Case control studies Minimum reporting requirements Non-random samples
The book concludes with a glossary that outlines key terms, and an extensive bibliography with several hundred citations directing readers to resources for further study.

Presented in an easy-to-follow style, Common Errors in Statistics, Fourth Edition is an excellent book for students and professionals in industry, government, medicine, and the social sciences.
Introduction to Statistics Through Resampling Methods and R
AvPhillip I. Good
Häftad, Engelska, 2013
745 kr
Skickas inom 5-8 vardagar
A highly accessible alternative approach to basic statistics Praise for the First Edition: "Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see . . . it would make a good nightstand book for every statistician."—Technometrics Written in a highly accessible style, Introduction to Statistics through Resampling Methods and R, Second Edition guides students in the understanding of descriptive statistics, estimation, hypothesis testing, and model building. The book emphasizes the discovery method, enabling readers to ascertain solutions on their own rather than simply copy answers or apply a formula by rote. The Second Edition utilizes the R programming language to simplify tedious computations, illustrate new concepts, and assist readers in completing exercises. The text facilitates quick learning through the use of: More than 250 exercises—with selected "hints"—scattered throughout to stimulate readers' thinking and to actively engage them in applying their newfound skills An increased focus on why a method is introduced Multiple explanations of basic concepts Real-life applications in a variety of disciplines Dozens of thought-provoking, problem-solving questions in the final chapter to assist readers in applying statistics to real-life applications Introduction to Statistics through Resampling Methods and R, Second Edition is an excellent resource for students and practitioners in the fields of agriculture, astrophysics, bacteriology, biology, botany, business, climatology, clinical trials, economics, education, epidemiology, genetics, geology, growth processes, hospital administration, law, manufacturing, marketing, medicine, mycology, physics, political science, psychology, social welfare, sports, and toxicology who want to master and learn to apply statistical methods.
Introduction to Statistics Through Resampling Methods and R
AvPhillip I. Good
E-bok
PDF, Engelska, 2013
883 kr
Läs direkt efter köp
A highly accessible alternative approach to basic statistics Praise for the First Edition: "Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see . . . it would make a good nightstand book for every statistician."—Technometrics Written in a highly accessible style, Introduction to Statistics through Resampling Methods and R, Second Edition guides students in the understanding of descriptive statistics, estimation, hypothesis testing, and model building. The book emphasizes the discovery method, enabling readers to ascertain solutions on their own rather than simply copy answers or apply a formula by rote. The Second Edition utilizes the R programming language to simplify tedious computations, illustrate new concepts, and assist readers in completing exercises. The text facilitates quick learning through the use of: More than 250 exercises—with selected "hints"—scattered throughout to stimulate readers'' thinking and to actively engage them in applying their newfound skills An increased focus on why a method is introduced Multiple explanations of basic concepts Real-life applications in a variety of disciplines Dozens of thought-provoking, problem-solving questions in the final chapter to assist readers in applying statistics to real-life applications Introduction to Statistics through Resampling Methods and R, Second Edition is an excellent resource for students and practitioners in the fields of agriculture, astrophysics, bacteriology, biology, botany, business, climatology, clinical trials, economics, education, epidemiology, genetics, geology, growth processes, hospital administration, law, manufacturing, marketing, medicine, mycology, physics, political science, psychology, social welfare, sports, and toxicology who want to master and learn to apply statistical methods.
Introduction to Statistics Through Resampling Methods and R
AvPhillip I. Good
E-bok
Engelska, 2012
861 kr
Läs direkt efter köp
A highly accessible alternative approach to basic statistics Praise for the First Edition: "Certainly one of the most impressive little paperback 200-page introductory statistics books that I will ever see . . . it would make a good nightstand book for every statistician."—Technometrics Written in a highly accessible style, Introduction to Statistics through Resampling Methods and R, Second Edition guides students in the understanding of descriptive statistics, estimation, hypothesis testing, and model building. The book emphasizes the discovery method, enabling readers to ascertain solutions on their own rather than simply copy answers or apply a formula by rote. The Second Edition utilizes the R programming language to simplify tedious computations, illustrate new concepts, and assist readers in completing exercises. The text facilitates quick learning through the use of: More than 250 exercises—with selected "hints"—scattered throughout to stimulate readers'' thinking and to actively engage them in applying their newfound skills An increased focus on why a method is introduced Multiple explanations of basic concepts Real-life applications in a variety of disciplines Dozens of thought-provoking, problem-solving questions in the final chapter to assist readers in applying statistics to real-life applications Introduction to Statistics through Resampling Methods and R, Second Edition is an excellent resource for students and practitioners in the fields of agriculture, astrophysics, bacteriology, biology, botany, business, climatology, clinical trials, economics, education, epidemiology, genetics, geology, growth processes, hospital administration, law, manufacturing, marketing, medicine, mycology, physics, political science, psychology, social welfare, sports, and toxicology who want to master and learn to apply statistical methods.
A-Z of Error-Free Research
AvPhillip I. Good
Inbunden, Engelska, 2018
2 529 kr
Skickas inom 10-15 vardagar
A Practical Guide with Step-by-Step Explanations, Numerous Worked Examples, and R CodeThe A–Z of Error-Free Research describes the design, analysis, modeling, and reporting of experiments, clinical trials, and surveys. The book shows you when to use statistics, the best ways to cope with variation, and how to design an experiment, determine optimal sample size, and collect useable data. It also helps you choose the best statistical procedures for your application and takes you step by step through model development and reporting results for publication.Transition from Student to ResearcherHelping you become a confident researcher, the book begins with an overview of when—and when not—to use statistics. It guides you through the planning and data collection phases and presents various data analysis techniques, including methods for sample size determination. The author then covers techniques for developing models that provide a basis for future research. He also discusses reporting techniques to ensure your research efforts get the proper credit. The book concludes with case-control and cohort studies.
A-Z of Error-Free Research
AvPhillip I. Good
Häftad, Engelska, 2012
916 kr
Skickas inom 10-15 vardagar
A Practical Guide with Step-by-Step Explanations, Numerous Worked Examples, and R CodeThe A–Z of Error-Free Research describes the design, analysis, modeling, and reporting of experiments, clinical trials, and surveys. The book shows you when to use statistics, the best ways to cope with variation, and how to design an experiment, determine optimal sample size, and collect useable data. It also helps you choose the best statistical procedures for your application and takes you step by step through model development and reporting results for publication.Transition from Student to ResearcherHelping you become a confident researcher, the book begins with an overview of when—and when not—to use statistics. It guides you through the planning and data collection phases and presents various data analysis techniques, including methods for sample size determination. The author then covers techniques for developing models that provide a basis for future research. He also discusses reporting techniques to ensure your research efforts get the proper credit. The book concludes with case-control and cohort studies.
Permutation, Parametric, and Bootstrap Tests of Hypotheses
AvPhillip I. Good
Häftad, Engelska, 2010
1 750 kr
Skickas inom 5-8 vardagar
This text is intended to provide a strong theoretical background in testing hypotheses and decision theory for those who will be practicing in the real worldorwhowillbeparticipatinginthetrainingofreal-worldstatisticiansand biostatisticians. In previous editions of this text, my rhetoric was somewhat tentative. I was saying, in e?ect, “Gee guys, permutation methods provide a practical real-world alternative to asymptotic parametric approximations. Why not give them a try?” But today, the theory, the software, and the hardware have come together. Distribution-free permutation procedures are the primary method for testing hypotheses. Parametric procedures and the bootstrap are to be reserved for the few situations in which they may be applicable. Four factors have forced this change: 1. Desire by workers in applied ?elds to use the most powerful statistic for their applications. Such workers may not be aware of the fundamental lemma of Neyman and Pearson, but they know that the statistic they wanttouse—acomplexscoreoraratioofscores,doesnothaveanalready well-tabulated distribution. 2. Pressure from regulatory agencies for the use of methods that yield exact signi?cance levels, not approximations. 3. A growing recognition that most real-world data are drawn from mixtures of populations. 4. A growing recognition that missing data is inevitable, balanced designs the exception. Thus, it seems natural that the theory of testing hypothesis and the more general decision theory in which it is embedded should be introduced via the permutation tests. On the other hand, certain relatively robust param- ric tests such as Student’s t continue to play an essential role in statistical practice.
Resampling Methods
A Practical Guide to Data Analysis
AvPhilip Good,Phillip I. Good
E-bok
PDF, Engelska, 2013
1 136 kr
Läs direkt efter köp
"Most introductory statistics books ignore or give little attention to resampling methods, and thus another generation learns the less than optimal methods of statistical analysis. Good attempts to remedy this situation by writing an introductory text that focuses on resampling methods, and he does it well."
— Ron C. Fryxell, Albion College
"...The wealth of the bibliography covers a wide range of disciplines."
---Dr. Dimitris Karlis, Athens University of Economics
This thoroughly revised second edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. It is an essential resource for industrial statisticians, statistical consultants, and research professionals in science, engineering, and technology.
Only requiring minimal mathematics beyond algebra, it provides a table-free introduction to data analysis utilizing numerous exercises, practical data sets, and freely available statistical shareware.
Topics and Features:
* Offers more practical examples plus an additional chapter dedicated to regression and data mining techniques and their limitations
* Uses resampling approach to introduction statistics
* A practical presentation that covers all three sampling methods: bootstrap, density-estimation, and permutations
* Includes systematic guide to help one select the correct procedure for a particular application
* Detailed coverage of all three statistical methodologies: classification, estimation, and hypothesis testing
* Suitable for classroom use and individual, self-study purposes
* Numerous practical examples using popular computer programs such as SAS®, Stata®, and StatXact®
* Useful appendixes with computer programs and code to develop individualized methods
* Downloadable freeware from author’s website:http://users.oco.net/drphilgood/resamp.htm
With its accessible style and intuitive topic development, the book is an excellent basic resource for the power, simplicity, and versatility of the bootstrap, cross-validation, and permutation tests. Students, professionals, and researchers will find it a prarticularly useful handbook for modern resampling methods and their applications.
Resampling Methods
A Practical Guide to Data Analysis
AvPhillip I. Good
E-bok
PDF, Engelska, 2013
1 136 kr
Läs direkt efter köp
"Most introductory statistics books ignore or give little attention to resampling methods, and thus another generation learns the less than optimal methods of statistical analysis. Good attempts to remedy this situation by writing an introductory text that focuses on resampling methods, and he does it well."
— Ron C. Fryxell, Albion College
"...The wealth of the bibliography covers a wide range of disciplines."
---Dr. Dimitris Karlis, Athens University of Economics
This thoroughly revised second edition is a practical guide to data analysis using the bootstrap, cross-validation, and permutation tests. It is an essential resource for industrial statisticians, statistical consultants, and research professionals in science, engineering, and technology.
Only requiring minimal mathematics beyond algebra, it provides a table-free introduction to data analysis utilizing numerous exercises, practical data sets, and freely available statistical shareware.
Topics and Features:
* Offers more practical examples plus an additional chapter dedicated to regression and data mining techniques and their limitations
* Uses resampling approach to introduction statistics
* A practical presentation that covers all three sampling methods: bootstrap, density-estimation, and permutations
* Includes systematic guide to help one select the correct procedure for a particular application
* Detailed coverage of all three statistical methodologies: classification, estimation, and hypothesis testing
* Suitable for classroom use and individual, self-study purposes
* Numerous practical examples using popular computer programs such as SAS®, Stata®, and StatXact®
* Useful appendixes with computer programs and code to develop individualized methods
* Downloadable freeware from author’s website:http://users.oco.net/drphilgood/resamp.htm
With its accessible style and intuitive topic development, the book is an excellent basic resource for the power, simplicity, and versatility of the bootstrap, cross-validation, and permutation tests. Students, professionals, and researchers will find it a prarticularly useful handbook for modern resampling methods and their applications.

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Phillip I. Good – författare

Permutation, Parametric, and Bootstrap Tests of Hypotheses

Permutation, Parametric, and Bootstrap Tests of Hypotheses

Common Errors in Statistics (and How to Avoid Them)

Analyzing the Large Number of Variables in Biomedical and Satellite Imagery

Analyzing the Large Number of Variables in Biomedical and Satellite Imagery

Introduction to Statistics Through Resampling Methods and Microsoft Office Excel

Introduction to Statistics Through Resampling Methods and Microsoft Office Excel

Manager's Guide to the Design and Conduct of Clinical Trials

Manager's Guide to the Design and Conduct of Clinical Trials

Common Errors in Statistics (and How to Avoid Them)

Resampling Methods

Resampling Methods

Analyzing the Large Number of Variables in Biomedical and Satellite Imagery

Common Errors in Statistics (and How to Avoid Them)

Common Errors in Statistics (and How to Avoid Them)

Common Errors in Statistics (and How to Avoid Them)

Common Errors in Statistics (and How to Avoid Them)

Introduction to Statistics Through Resampling Methods and R

Introduction to Statistics Through Resampling Methods and R

Introduction to Statistics Through Resampling Methods and R

A-Z of Error-Free Research

A-Z of Error-Free Research

Permutation, Parametric, and Bootstrap Tests of Hypotheses

Resampling Methods

Resampling Methods

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