Practical Stats: Helsel-2012
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Title
| Statistics for Censored Environmental Data Using Minitab and R |
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Author
| Helsel, Dennis R. |
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Abstract/Summary Statement
| This book introduces methods for censored data, some simple and some more complex, to potential users who until now were not aware of their existence, or perhaps not aware of their utility. These methods are directly applicable to air quality, water quality, soils, and contaminates in biota, among other types of data. Most of the methods come from the field of survival analysis, where the primary variable being investigated is length of time. Here they are instead applied to environmental measures such as concentration. The first edition (under the name Nondetects And Data Analysis) has influenced the methods used by scientists in several disciplines, as reflected in guidance documents and usage in journals. |
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Table of Contents
| Introduction Chapters: 1. Things People Do with Censored Data that are Just Wrong 2. Three Approaches for Censored Data 3. Reporting Limits 4. Reporting, Storing, and Using Censored Data 5. Plotting Censored Data 6. Computing Summary Statistics and Totals 7. Computing Interval Estimates 8. What Can Be Done When All Data Are Below the Reporting Limit? 9. Comparing Two Groups 10. Comparing Three or More Groups 11. Correlation 12. Regression and Trends 13. Multivariate Methods for Censored Data 14. The NADA for R Software Appendix References Index |
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Citation
| Helsel, D.R., 2012, Statistics for Censored Environmental Data Using Minitab and R, second edition. John Wiley and Sons, Inc: Hoboken, NJ, 250 pp. |
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Method Source
| Practical Stats |
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Source Organization Country
| USA |
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Publication Year
| 2012 |
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Special Notes
| There is a website that is linked to this book, at http://practicalstats.com/nada, that provides: 1. answers to exercies computed 2. Minitab macros and R scripts 3. link to NADA for R package 4. datasets used in book 5. errata sheet |
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Item Type
| Book |
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Publication Source Type
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Other Additional information: Company, Practical Stats, Castle Rock, CO |
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Purpose
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Data analysis |
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Design or Data Analysis Objectives
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Compliance with a threshold Derive thresholds Exploring/summarizing data Relationships & correlations Revisit Spatial trends Temporal trends Volume calculations |
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Complexity
| Medium |
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Media Emphasized
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Air Biological Groundwater Soils/Sediment Surface Water |
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Media Subcategory
| |
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Special Topics
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Characterizing the uncertainty of an estimated value Evaluating whether data follow a certain (e.g., normal) distribution Handling nondetects Identifying outliers |
