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[null,"1.","Record Nr.",null,"UNINA9910826753703321"]
[null,null,"Autore",null,"Ofungwu Joseph"]
[null,null,"Titolo",null,"Statistical applications for environmental analysis and risk assessment / / Joseph Ofungwu"]
[null,null,"Pubbl/distr/stampa",null,"Hoboken, New Jersey : , : John Wiley & Sons, , 2014"]
[{"$nulls":4},"2014"]
[null,null,"ISBN",null,"1-118-63446-2"]
[null,null,"Descrizione fisica",null,"1 online resource (648 p.)"]
[null,null,"Collana",null,"Wiley Series in Statistics in Practice"]
[null,null,"Classificazione",null,"519.15"]
[{"$nulls":4},"363.7/02"]
[null,null,"Disciplina",null,"363.7/02"]
[null,null,"Soggetti",null,"Environmental risk assessment - Statistical methods"]
[null,null,"Lingua di pubblicazione",null,"Inglese"]
[null,null,"Formato",null,"Materiale a stampa"]
[null,null,null,"Livello bibliografico","Monografia"]
[null,null,null,"Note generali","Includes bibliographical references (p. 609-612) and index"]
[null,null,null,"Nota di bibliografia","Includes bibliographical references and index."]
[null,null,"Nota di contenuto",null,"Statistical Applications for Environmental Analysis and Risk Assessment; Contents; Preface; Acknowledgements; 1. Introduction; 1.1 Introduction and Overview; 1.2 The Aim of the Book: Get Involved!; 1.3 The Approach and Style: Clarity, Clarity, Clarity; Part I: Basic Statistical Measures and Concepts; 2. Introduction to Software Packages used in this Book; 2.1 R; 2.1.1 Helpful R Tips; 2.1.2 Disadvantages of R; 2.2 ProUCL; 2.2.1 Helpful ProUCL Tips; 2.2.2 Potential Deficiencies of ProUCL; 2.3 Visual Sample Plan; 2.4 DATAPLOT; 2.4.1 Helpful Tips for Running DATAPLOT in Batch Mode"]
[{"$nulls":4},"2.5 Kendall-Thiel Robust Line2.6 Minitab®; 2.7 Microsoft Excel; 3. Laboratory Detection Limits, Non-Detects and Data Analysis; 3.1 Introduction and Overview; 3.2 Types of Laboratory Data Detection Limits; 3.3 Problems with Nondetects in Statistical Data Samples; 3.4 Options for Addressing Nondetects in Data Analysis; 3.4.1 Kaplan-Meier Estimation; 3.4.2 Robust Regression on Order Statistics; 3.4.3 Maximum Likelihood Estimation; 4. Data Sample, Data Population and Data Distribution; 4.1 Introduction and Overview; 4.2 Data Sample Versus Data Population or Universe"]
[{"$nulls":4},"4.3 The Concept of a Distribution4.3.1 The Concept of a Probability Distribution Function; 4.3.2 Cumulative Probability Distribution and Empirical Cumulative Distribution Functions; 4.4 Types of Distributions; 4.4.1 Normal Distribution; 4.4.1.1 Goodness-of-Fit (GOF) Tests for the Normal Distribution; 4.4.1.2 Central Limit Theorem; 4.4.2 Lognormal, Gamma, and Other Continuous Distributions; 4.4.2.1 Gamma Distribution; 4.4.2.2 Logistic Distribution; 4.4.2.3 Other Continuous "]
[{"$nulls":4},"Distributions; 4.4.3 Distributions Used in Inferential Statistics (Student's t, Chi-Square, F)"]
[{"$nulls":4},"4.4.3.1 Student's t Distribution4.4.3.2 Chi-Square Distribution; 4.4.3.3 F Distribution; 4.4.4 Discrete Distributions; 4.4.4.1 Binomial Distribution; 4.4.4.2 Poisson Distribution; Exercises; 5. Graphics for Data Analysis and Presentation; 5.1 Introduction and Overview; 5.2 Graphics for Single Univariate Data Samples; 5.2.1 Box and Whiskers Plot; 5.2.2 Probability Plots (i.e., Quantile-Quantile Plots for Comparing a Data Sample to a Theoretical Distribution); 5.2.3 Quantile Plots; 5.2.4 Histograms and Kernel Density Plots; 5.3 Graphics for Two or More Univariate Data Samples"]
[{"$nulls":4},"5.3.1 Quantile-Quantile Plots for Comparing Two Univariate Data Samples5.3.2 Side-by-Side Box Plots; 5.4 Graphics for Bivariate and Multivariate Data Samples; 5.4.1 Graphical Data Analysis for Bivariate Data Samples; 5.4.2 Graphical Data Analysis for Multivariate Data Samples; 5.5 Graphics for Data Presentation; 5.6 Data Smoothing; 5.6.1 Moving Average and Moving Median Smoothing; 5.6.2 Locally Weighted Scatterplot Smoothing (LOWESS or LOESS); 5.6.2.1 Smoothness Factor and the Degree of the Local Regression; 5.6.2.2 Basic and Robust LOWESS Weighting Functions"]
[{"$nulls":4},"5.6.2.3 LOESS Scatterplot Smoothing for Data with Multiple Variables"]
[null,null,null,"Sommario/riassunto","Statistical Applications for Environmental Analysis and Risk Assessment guides readers through real-world situations and the best statistical methods used to determine the nature and extent of the problem, evaluate the potential human health and ecological risks, and design and implement remedial systems as necessary. Featuring numerous worked examples using actual data and \"ready-made\" software scripts, Statistical Applications for Environmental Analysis and Risk Assessment also includes:   Descriptions of basic statistical concepts and principles in an informal style t"]