Using statistical methods for water quality management [[electronic resource] ] : issues, problems, and solutions / / Graham B. McBride |
Autore | McBride Graham B. <1948-> |
Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2005 |
Descrizione fisica | 1 online resource (343 p.) |
Disciplina | 628.1/61 |
Collana | Wiley series in statistics in practice |
Soggetto topico |
Water quality - Measurement - Statistical methods
Water quality management - Statistical methods |
ISBN |
1-280-27693-2
9786610276936 0-470-35778-9 0-471-73319-9 0-471-73320-2 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Using Statistical Methods for Water Quality Management; Contents; List of Figures; List of Figures; List of Tables; List of Tables; Preface; Part I Issues; 1 Introduction; 1.1 Conventions; 1.2 The essentials; 1.3 Meeting management's information needs; 1.4 Water quality observations as random variables; 1.5 Samples and populations; 1.6 Special characteristics of water quality data; Accurate observations are both precise and unbiased; 1.7 Data analysis protocols; 2 Basic concepts of probability and statistics; 2.1 Probability rules; 2.2 Representing data; 2.2.1 Types of data
2.2.2 Frequency, bar graph, and histogramMost probable number (MPN) data for shelljish-growing waters; 2.2.3 Describing the distribution of probability; Bar graph of MPN data; 2.2.4 Discrete versus continuous data; Cumulative distribution function of MPN data; 2.2.5 Summary statistics; Summary of terms for sample data; Summary of terms for populations; 2.3 Exploratory and graphical methods; Symmetry and skewness; Lowess fit through data for the Ngakaroa Stream; 2.4 Important distributions; Boxplot for somatic coliphage in recreational waters; 2.5 Continuous distributions 2.5.1 Normal distributionProbability density function (pdf) for the unit normal distribution; Cumulative distribution function (CDF) for the unit normal distribution; 2.5.2 Lognormal distribution; 2.5.3 Gamma distribution; Normal and lognormal probability density functions; 2.5.4 Beta distribution; A variety of shapes for the pdf of the two-parameter gamma distribution; 2.6 Discrete distributions; 2.6.1 Binomial distribution; A variety of shapes for the pdf of the two-parameter beta distribution; Probability mass functions for three common discrete distributions; 2.6.2 Poisson distribution 2.6.3 Negative binomial distribution2.6.4 Hypergeometric distribution; 2.6.5 Multinomial distribution; 2.7 Sampling distributions; 2.7.1 Student's t-distribution; 2.7.2 Chi-square distribution; Student t-distributions and the unit normal distribution; 2.7.3 F-distribution; 2.8 Statistical tables; Probability density functions for the x2- and F-distributions; Five possibilities for reporting areas under the t-distribution; 2.9 Correlation and measures thereof; Possible linear correlations; 2.10 Statistical models and model parameters; 2.11 Serial correlation, seasonality, trend, and scale 2.11.1 Effect of serial correlationField Raynes effluent suspended solids data and serial correlation structure; 2.12 Regression; 2.12.1 Applications to water quality; 2.12.2 Nonparametric regression; 2.13 Estimating model parameters; 2.13.1 Point versus interval estimation; 2.13.2 Interval estimates; 2.13.3 Bias; 2.13.4 Percentiles; Problems; Appendix: Conditional probabilities-The Monty Hall dilemma; 3 Intervals; 3.1 Confidence intervals; 3.1.1 For means; Geometric mean confidence limits as a function of sample size; 3.1.2 For prediction; ""Error bars''; 3.1.3 For percentiles Prediction intervals and confidence intervals for linear regression |
Record Nr. | UNINA-9910145038203321 |
McBride Graham B. <1948-> | ||
Hoboken, N.J., : Wiley-Interscience, c2005 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|
Using statistical methods for water quality management : issues, problems, and solutions / / Graham B. McBride |
Autore | McBride Graham B. <1948-> |
Edizione | [1st ed.] |
Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2005 |
Descrizione fisica | 1 online resource (343 p.) |
Disciplina | 628.1/61 |
Collana | Wiley series in statistics in practice |
Soggetto topico |
Water quality - Measurement - Statistical methods
Water quality management - Statistical methods |
ISBN |
1-280-27693-2
9786610276936 0-470-35778-9 0-471-73319-9 0-471-73320-2 |
Formato | Materiale a stampa |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Using Statistical Methods for Water Quality Management; Contents; List of Figures; List of Figures; List of Tables; List of Tables; Preface; Part I Issues; 1 Introduction; 1.1 Conventions; 1.2 The essentials; 1.3 Meeting management's information needs; 1.4 Water quality observations as random variables; 1.5 Samples and populations; 1.6 Special characteristics of water quality data; Accurate observations are both precise and unbiased; 1.7 Data analysis protocols; 2 Basic concepts of probability and statistics; 2.1 Probability rules; 2.2 Representing data; 2.2.1 Types of data
2.2.2 Frequency, bar graph, and histogramMost probable number (MPN) data for shelljish-growing waters; 2.2.3 Describing the distribution of probability; Bar graph of MPN data; 2.2.4 Discrete versus continuous data; Cumulative distribution function of MPN data; 2.2.5 Summary statistics; Summary of terms for sample data; Summary of terms for populations; 2.3 Exploratory and graphical methods; Symmetry and skewness; Lowess fit through data for the Ngakaroa Stream; 2.4 Important distributions; Boxplot for somatic coliphage in recreational waters; 2.5 Continuous distributions 2.5.1 Normal distributionProbability density function (pdf) for the unit normal distribution; Cumulative distribution function (CDF) for the unit normal distribution; 2.5.2 Lognormal distribution; 2.5.3 Gamma distribution; Normal and lognormal probability density functions; 2.5.4 Beta distribution; A variety of shapes for the pdf of the two-parameter gamma distribution; 2.6 Discrete distributions; 2.6.1 Binomial distribution; A variety of shapes for the pdf of the two-parameter beta distribution; Probability mass functions for three common discrete distributions; 2.6.2 Poisson distribution 2.6.3 Negative binomial distribution2.6.4 Hypergeometric distribution; 2.6.5 Multinomial distribution; 2.7 Sampling distributions; 2.7.1 Student's t-distribution; 2.7.2 Chi-square distribution; Student t-distributions and the unit normal distribution; 2.7.3 F-distribution; 2.8 Statistical tables; Probability density functions for the x2- and F-distributions; Five possibilities for reporting areas under the t-distribution; 2.9 Correlation and measures thereof; Possible linear correlations; 2.10 Statistical models and model parameters; 2.11 Serial correlation, seasonality, trend, and scale 2.11.1 Effect of serial correlationField Raynes effluent suspended solids data and serial correlation structure; 2.12 Regression; 2.12.1 Applications to water quality; 2.12.2 Nonparametric regression; 2.13 Estimating model parameters; 2.13.1 Point versus interval estimation; 2.13.2 Interval estimates; 2.13.3 Bias; 2.13.4 Percentiles; Problems; Appendix: Conditional probabilities-The Monty Hall dilemma; 3 Intervals; 3.1 Confidence intervals; 3.1.1 For means; Geometric mean confidence limits as a function of sample size; 3.1.2 For prediction; ""Error bars''; 3.1.3 For percentiles Prediction intervals and confidence intervals for linear regression |
Record Nr. | UNINA-9910828704303321 |
McBride Graham B. <1948-> | ||
Hoboken, N.J., : Wiley-Interscience, c2005 | ||
Materiale a stampa | ||
Lo trovi qui: Univ. Federico II | ||
|