The second edition of this bestseller is 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 so that each one can 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…mehr
The second edition of this bestseller is 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 so that each one can 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.
Chapter topics include: Environmental Problems and Statistics. A Brief Review of Statistics. Plotting Data. Smoothing Data. Seeing the Shape of a Distribution. External Reference Distributions. Accuracy, Bias, and Precision of Measurements. Precision of Calculated Values. Fundamentals of Process Control Charts. Specialized Control Charts. Limit of Detection. Censored Data. Paired t -Test for Assessing the Average of Differences. Independent t-Test for Assessing the Difference of Two Averages. Multiple Paired Comparison of k Averages. 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.Correlation. Serial Correlation. The Method of Least Squares. Precision of Parameters in Linear Models. Precision of Parameters in Nonlinear Models. Weighted Least Squares. Empirical Model Building by Linear Regression. The Coefficient of Determination, R2. Data Adjustment for Process Rationalization. How Measurement Errors Propagate into Calculated Values. Using Simulations to Study Statistical Problems. Introduction to Time Series Modeling. Forecasting Time Series. Intervention Analysis. Appendix-Statistical Tables.
Chapter topics include: Environmental Problems and Statistics. A Brief Review of Statistics. Plotting Data. Smoothing Data. Seeing the Shape of a Distribution. External Reference Distributions. Accuracy, Bias, and Precision of Measurements. Precision of Calculated Values. Fundamentals of Process Control Charts. Specialized Control Charts. Limit of Detection. Censored Data. Paired t -Test for Assessing the Average of Differences. Independent t-Test for Assessing the Difference of Two Averages. Multiple Paired Comparison of k Averages. 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.Correlation. Serial Correlation. The Method of Least Squares. Precision of Parameters in Linear Models. Precision of Parameters in Nonlinear Models. Weighted Least Squares. Empirical Model Building by Linear Regression. The Coefficient of Determination, R2. Data Adjustment for Process Rationalization. How Measurement Errors Propagate into Calculated Values. Using Simulations to Study Statistical Problems. Introduction to Time Series Modeling. Forecasting Time Series. Intervention Analysis. Appendix-Statistical Tables.
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