**Author**: Gerald J. Hahn

**Publisher:**John Wiley & Sons

**ISBN:**0470317442

**Category :**Mathematics

**Languages :**en

**Pages :**423

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## Statistical Intervals

**Author**: Gerald J. Hahn

**Publisher:** John Wiley & Sons

**ISBN:** 0470317442

**Category : **Mathematics

**Languages : **en

**Pages : **423

**Book Description**

Presents a detailed exposition of statistical intervals and emphasizes applications in industry. The discussion differentiates at an elementary level among different kinds of statistical intervals and gives instruction with numerous examples and simple math on how to construct such intervals from sample data. This includes confidence intervals to contain a population percentile, confidence intervals on probability of meeting specified threshold value, and prediction intervals to include observation in a future sample. Also has an appendix containing computer subroutines for nonparametric statistical intervals.

## Statistical Intervals

**Author**: Gerald J. Hahn

**Publisher:** John Wiley & Sons

**ISBN:** 0470317442

**Category : **Mathematics

**Languages : **en

**Pages : **423

**Book Description**

Presents a detailed exposition of statistical intervals and emphasizes applications in industry. The discussion differentiates at an elementary level among different kinds of statistical intervals and gives instruction with numerous examples and simple math on how to construct such intervals from sample data. This includes confidence intervals to contain a population percentile, confidence intervals on probability of meeting specified threshold value, and prediction intervals to include observation in a future sample. Also has an appendix containing computer subroutines for nonparametric statistical intervals.

## Statistical Intervals

**Author**: William Q. Meeker

**Publisher:** John Wiley & Sons

**ISBN:** 1118594959

**Category : **Mathematics

**Languages : **en

**Pages : **648

**Book Description**

Describes statistical intervals to quantify sampling uncertainty,focusing on key application needs and recently developed methodology in an easy-to-apply format Statistical intervals provide invaluable tools for quantifying sampling uncertainty. The widely hailed first edition, published in 1991, described the use and construction of the most important statistical intervals. Particular emphasis was given to intervals—such as prediction intervals, tolerance intervals and confidence intervals on distribution quantiles—frequently needed in practice, but often neglected in introductory courses. Vastly improved computer capabilities over the past 25 years have resulted in an explosion of the tools readily available to analysts. This second edition—more than double the size of the first—adds these new methods in an easy-to-apply format. In addition to extensive updating of the original chapters, the second edition includes new chapters on: Likelihood-based statistical intervals Nonparametric bootstrap intervals Parametric bootstrap and other simulation-based intervals An introduction to Bayesian intervals Bayesian intervals for the popular binomial, Poisson and normal distributions Statistical intervals for Bayesian hierarchical models Advanced case studies, further illustrating the use of the newly described methods New technical appendices provide justification of the methods and pathways to extensions and further applications. A webpage directs readers to current readily accessible computer software and other useful information. Statistical Intervals: A Guide for Practitioners and Researchers, Second Edition is an up-to-date working guide and reference for all who analyze data, allowing them to quantify the uncertainty in their results using statistical intervals.

## Statistical Intervals

**Author**: William Q. Meeker

**Publisher:** John Wiley & Sons

**ISBN:** 0471687170

**Category : **Mathematics

**Languages : **en

**Pages : **648

**Book Description**

Describes statistical intervals to quantify sampling uncertainty,focusing on key application needs and recently developed methodology in an easy-to-apply format Statistical intervals provide invaluable tools for quantifying sampling uncertainty. The widely hailed first edition, published in 1991, described the use and construction of the most important statistical intervals. Particular emphasis was given to intervals—such as prediction intervals, tolerance intervals and confidence intervals on distribution quantiles—frequently needed in practice, but often neglected in introductory courses. Vastly improved computer capabilities over the past 25 years have resulted in an explosion of the tools readily available to analysts. This second edition—more than double the size of the first—adds these new methods in an easy-to-apply format. In addition to extensive updating of the original chapters, the second edition includes new chapters on: Likelihood-based statistical intervals Nonparametric bootstrap intervals Parametric bootstrap and other simulation-based intervals An introduction to Bayesian intervals Bayesian intervals for the popular binomial, Poisson and normal distributions Statistical intervals for Bayesian hierarchical models Advanced case studies, further illustrating the use of the newly described methods New technical appendices provide justification of the methods and pathways to extensions and further applications. A webpage directs readers to current readily accessible computer software and other useful information. Statistical Intervals: A Guide for Practitioners and Researchers, Second Edition is an up-to-date working guide and reference for all who analyze data, allowing them to quantify the uncertainty in their results using statistical intervals.

## Statistical Applications for Environmental Analysis and Risk Assessment

**Author**: Joseph Ofungwu

**Publisher:** John Wiley & Sons

**ISBN:** 1118634519

**Category : **Social Science

**Languages : **en

**Pages : **648

**Book Description**

Statistical Applications for Environmental Analysis and RiskAssessment guides readers through real-world situations and thebest statistical methods used to determine the nature and extent ofthe problem, evaluate the potential human health and ecologicalrisks, and design and implement remedial systems as necessary.Featuring numerous worked examples using actual data and“ready-made” software scripts, StatisticalApplications for Environmental Analysis and Risk Assessmentalso includes: • Descriptions of basic statistical concepts andprinciples in an informal style that does not presume priorfamiliarity with the subject • Detailed illustrations of statistical applications inthe environmental and related water resources fields usingreal-world data in the contexts that would typically be encounteredby practitioners • Software scripts using the high-powered statisticalsoftware system, R, and supplemented by USEPA’s ProUCL andUSDOE’s VSP software packages, which are all freelyavailable • Coverage of frequent data sample issues such asnon-detects, outliers, skewness, sustained and cyclical trend thathabitually plague environmental data samples • Clear demonstrations of the crucial, but oftenoverlooked, role of statistics in environmental sampling design andsubsequent exposure risk assessment.

## Statistical Analysis of Magnetic Profiles and Geomagnetic Reversal Sequences

**Author**: Jeffrey D. Phillips

**Publisher:**

**ISBN:**

**Category : **Geomagnetic reversals

**Languages : **en

**Pages : **268

**Book Description**

## Statistical Intervals

**Author**: Gerald J. Hahn

**Publisher:** Wiley-Interscience

**ISBN:**

**Category : **Mathematics

**Languages : **en

**Pages : **424

**Book Description**

Introduction, basic consepts, and assumptions; Overview of different of statistics intervals; Constructing statistical intervals assuming a normal distribution using simple tabulations; Methods for calculating statistical intervals for a normal distribution; Distribution-free statistical intervals; Statistical intervals for proportions and percentages (Binomial Distribution); Statistical intervals for the number of occurrences (Poisson distribution); Sample size requirements for confidence intervals on population parameters; Sample size requirements for tolerance intervals, tolerance bounds, and demonstration tests; Samplesize requirements for prediction intervals; A review of other statistical intervals; Other methods for setting statistical intervals; Case studies.

## Statistics with Confidence

**Author**: Douglas Altman

**Publisher:** John Wiley & Sons

**ISBN:** 1118702506

**Category : **Medical

**Languages : **en

**Pages : **256

**Book Description**

This highly popular introduction to confidence intervals has been thoroughly updated and expanded. It includes methods for using confidence intervals, with illustrative worked examples and extensive guidelines and checklists to help the novice.

## Biostatistics

**Author**: Wayne W. Daniel

**Publisher:** Wiley

**ISBN:** 9780471588528

**Category : **Medical

**Languages : **en

**Pages : **814

**Book Description**

Like its predecessors, this edition stresses intuitive understanding of principles rather than learning by mathematical proof. Provides broad coverage of statistical procedures used in all the health science disciplines. This version contains a greater emphasis on computer applications (MINITAB command instruction is demonstrated) for most of the statistical techniques. New to this edition: computer printouts demonstrating the SAS® software package, determination of sample size to control Type I and Type II errors, the Fisher Exact Test, the Repeated Measures Design, the Mantel-Haenszel Statistic. More than 250 of the examples and exercises are based on actual data obtained directly from researchers in the health field and from reports of research findings published in health sciences literature.

## Confidence Intervals

**Author**: Michael Smithson

**Publisher:** SAGE

**ISBN:** 9780761924999

**Category : **Mathematics

**Languages : **en

**Pages : **104

**Book Description**

Smithson first introduces the basis of the confidence interval framework and then provides the criteria for "best" confidence intervals, along with the trade-offs between confidence and precision. Next, using a reader-friendly style with lots of worked out examples from various disciplines, he covers such pertinent topics as: the transformation principle whereby a confidence interval for a parameter may be used to construct an interval for any monotonic transformation of that parameter; confidence intervals on distributions whose shape changes with the value of the parameter being estimated; and, the relationship between confidence interval and significance testing frameworks, particularly regarding power.

## Transations of the Log Analysis Software Evaluation and Review (LASER) Symposium

**Author**:

**Publisher:**

**ISBN:**

**Category : **Oil well logging

**Languages : **en

**Pages : **

**Book Description**

eBook Journalism in PDF, ePub, Mobi and Kindle

Presents a detailed exposition of statistical intervals and emphasizes applications in industry. The discussion differentiates at an elementary level among different kinds of statistical intervals and gives instruction with numerous examples and simple math on how to construct such intervals from sample data. This includes confidence intervals to contain a population percentile, confidence intervals on probability of meeting specified threshold value, and prediction intervals to include observation in a future sample. Also has an appendix containing computer subroutines for nonparametric statistical intervals.

Presents a detailed exposition of statistical intervals and emphasizes applications in industry. The discussion differentiates at an elementary level among different kinds of statistical intervals and gives instruction with numerous examples and simple math on how to construct such intervals from sample data. This includes confidence intervals to contain a population percentile, confidence intervals on probability of meeting specified threshold value, and prediction intervals to include observation in a future sample. Also has an appendix containing computer subroutines for nonparametric statistical intervals.

Describes statistical intervals to quantify sampling uncertainty,focusing on key application needs and recently developed methodology in an easy-to-apply format Statistical intervals provide invaluable tools for quantifying sampling uncertainty. The widely hailed first edition, published in 1991, described the use and construction of the most important statistical intervals. Particular emphasis was given to intervals—such as prediction intervals, tolerance intervals and confidence intervals on distribution quantiles—frequently needed in practice, but often neglected in introductory courses. Vastly improved computer capabilities over the past 25 years have resulted in an explosion of the tools readily available to analysts. This second edition—more than double the size of the first—adds these new methods in an easy-to-apply format. In addition to extensive updating of the original chapters, the second edition includes new chapters on: Likelihood-based statistical intervals Nonparametric bootstrap intervals Parametric bootstrap and other simulation-based intervals An introduction to Bayesian intervals Bayesian intervals for the popular binomial, Poisson and normal distributions Statistical intervals for Bayesian hierarchical models Advanced case studies, further illustrating the use of the newly described methods New technical appendices provide justification of the methods and pathways to extensions and further applications. A webpage directs readers to current readily accessible computer software and other useful information. Statistical Intervals: A Guide for Practitioners and Researchers, Second Edition is an up-to-date working guide and reference for all who analyze data, allowing them to quantify the uncertainty in their results using statistical intervals.

Describes statistical intervals to quantify sampling uncertainty,focusing on key application needs and recently developed methodology in an easy-to-apply format Statistical intervals provide invaluable tools for quantifying sampling uncertainty. The widely hailed first edition, published in 1991, described the use and construction of the most important statistical intervals. Particular emphasis was given to intervals—such as prediction intervals, tolerance intervals and confidence intervals on distribution quantiles—frequently needed in practice, but often neglected in introductory courses. Vastly improved computer capabilities over the past 25 years have resulted in an explosion of the tools readily available to analysts. This second edition—more than double the size of the first—adds these new methods in an easy-to-apply format. In addition to extensive updating of the original chapters, the second edition includes new chapters on: Likelihood-based statistical intervals Nonparametric bootstrap intervals Parametric bootstrap and other simulation-based intervals An introduction to Bayesian intervals Bayesian intervals for the popular binomial, Poisson and normal distributions Statistical intervals for Bayesian hierarchical models Advanced case studies, further illustrating the use of the newly described methods New technical appendices provide justification of the methods and pathways to extensions and further applications. A webpage directs readers to current readily accessible computer software and other useful information. Statistical Intervals: A Guide for Practitioners and Researchers, Second Edition is an up-to-date working guide and reference for all who analyze data, allowing them to quantify the uncertainty in their results using statistical intervals.

Statistical Applications for Environmental Analysis and RiskAssessment guides readers through real-world situations and thebest statistical methods used to determine the nature and extent ofthe problem, evaluate the potential human health and ecologicalrisks, and design and implement remedial systems as necessary.Featuring numerous worked examples using actual data and“ready-made” software scripts, StatisticalApplications for Environmental Analysis and Risk Assessmentalso includes: • Descriptions of basic statistical concepts andprinciples in an informal style that does not presume priorfamiliarity with the subject • Detailed illustrations of statistical applications inthe environmental and related water resources fields usingreal-world data in the contexts that would typically be encounteredby practitioners • Software scripts using the high-powered statisticalsoftware system, R, and supplemented by USEPA’s ProUCL andUSDOE’s VSP software packages, which are all freelyavailable • Coverage of frequent data sample issues such asnon-detects, outliers, skewness, sustained and cyclical trend thathabitually plague environmental data samples • Clear demonstrations of the crucial, but oftenoverlooked, role of statistics in environmental sampling design andsubsequent exposure risk assessment.

Introduction, basic consepts, and assumptions; Overview of different of statistics intervals; Constructing statistical intervals assuming a normal distribution using simple tabulations; Methods for calculating statistical intervals for a normal distribution; Distribution-free statistical intervals; Statistical intervals for proportions and percentages (Binomial Distribution); Statistical intervals for the number of occurrences (Poisson distribution); Sample size requirements for confidence intervals on population parameters; Sample size requirements for tolerance intervals, tolerance bounds, and demonstration tests; Samplesize requirements for prediction intervals; A review of other statistical intervals; Other methods for setting statistical intervals; Case studies.

This highly popular introduction to confidence intervals has been thoroughly updated and expanded. It includes methods for using confidence intervals, with illustrative worked examples and extensive guidelines and checklists to help the novice.

Like its predecessors, this edition stresses intuitive understanding of principles rather than learning by mathematical proof. Provides broad coverage of statistical procedures used in all the health science disciplines. This version contains a greater emphasis on computer applications (MINITAB command instruction is demonstrated) for most of the statistical techniques. New to this edition: computer printouts demonstrating the SAS® software package, determination of sample size to control Type I and Type II errors, the Fisher Exact Test, the Repeated Measures Design, the Mantel-Haenszel Statistic. More than 250 of the examples and exercises are based on actual data obtained directly from researchers in the health field and from reports of research findings published in health sciences literature.

Smithson first introduces the basis of the confidence interval framework and then provides the criteria for "best" confidence intervals, along with the trade-offs between confidence and precision. Next, using a reader-friendly style with lots of worked out examples from various disciplines, he covers such pertinent topics as: the transformation principle whereby a confidence interval for a parameter may be used to construct an interval for any monotonic transformation of that parameter; confidence intervals on distributions whose shape changes with the value of the parameter being estimated; and, the relationship between confidence interval and significance testing frameworks, particularly regarding power.