Statistics for Environmental Engineers

ISBN-13: 9781566705929 / Angielski / Twarda / 2002 / 512 str.

Linfield C. Brown; P. Mac Berthouex; Berthouex Mac Berthouex

Opis

The second edition of this bestseller serves as an ideal textbook for students and a valuable reference for environmental scientists and engineers. Written in an easy-to-understand style, Statistics for Environmental Engineers, Second Edition consists of 54 short, "stand-alone" chapters. All chapters address a particular environmental problem or statistical technique and are written in a manner that permits each chapter to be studied independently and in any order. Chapters are organized around specific case studies, beginning with brief discussions of the appropriate methodologies, followed by analysis of the case study examples, and ending with comments on the strengths and weaknesses of the approaches.

Recenzje

"The book is well written, easy to read, and interesting, which is no small feat considering the subject matter. The authors have taken considerable steps to make this textbook user-friendly to their intended audience, environmental engineers. … The authors, both recognized experts in civil and sanitary engineering, provide data and problems in each chapter that use relevant and realistic examples to teach the concepts of each chapter. … [U]seful and well written … [the book] contains exercises based on the types of real-world problems that environmental engineers face on a daily basis."
- Environmental Practice, Vol. 6, No. 4, Dec. 2004


About the first edition:
"...a valuable addition to any environmental engineer's library."
-Technometrics

Spis treści

Environmental Problems and Statistics

A Brief Review of Statistics

Plotting Data

Smoothing Data

Seeing the Shape of a Distribution

External Reference Distributions

Using Transformations

Estimating Percentiles

Accuracy, Bias, and Precision of Measurements

Precision of Calculated Values

Laboratory Quality Assurance

Fundamentals of Process Control Charts

Specialized Control Charts

Limit of Detection

Analyzing Censored Data

Comparing a Mean with a Standard

Paired t -Test for Assessing the Average of Differences

Independent t-Test for Assessing the Difference of Two Averages

Assessing the Difference of Proportions

Multiple Paired Comparison of k Averages

Tolerance Intervals and Prediction Intervals

Experimental Design

Sizing the Experiment

Analysis of Variance to Compare k Averages

Components of Variance

Multiple Factor Analysis of Variance

Factorial Experimental Designs

Fractional Factorial Experimental Designs

Screening of Important Variables

Analyzing Factorial Experiments by Regression

Correlation

Serial Correlation

The Method of Least Squares

Precision of Parameter Estimates in Linear Models

Precision of Parameter Estimates in Nonlinear Models

Calibration

Weighted Least Squares

Empirical Model Building by Linear Regression

The Coefficient of Determination, R2

Regression Analysis with Categorical Variables

The Effect of Autocorrelation on Regression

The Iterative Approach to Experimentation

Seeking OptimumConditions by Response Surface Methodology

Designing Experiments for Nonlinear Parameter Estimation

Why Linearization Can Bias Parameter Estimates

A Problem in Fitting Models to Multiresponse Data

Model Discrimination

Data Adjustment for Process Rationalization

How Measurement Errors are Transmitted into Calculated Values

Using Simulations to Study Statistical Problems

Introduction to Time Series Modeling

Transfer Function Models

Forecasting Time Series

Intervention Analysis

Appendix-Statistical Tables

Index

O autorze

Linfield C. Brown, Paul Mac Berthouex