Can we coexist with the other life forms that have evolved on this planet? Are there realistic alternatives to fossil fuels that would sustainably provide for human society's energy needs and have fewer harmful effects? How do we deal with threats such as emergent diseases? Mathematical models—equations of various sorts capturing relationships between variables involved in a complex situation—are fundamental for understanding the potential consequences of choices we make. Extracting insights from the vast amounts of data we are able to collect requires analysis methods and statistical reasoning. This book on elementary topics in mathematical modeling and data analysis is intended for an undergraduate “liberal arts mathematics”-type course but with a specific focus on environmental applications. It is suitable for introductory courses with no prerequisites beyond high school mathematics. A great variety of exercises extends the discussions of the main text to new situations and/or introduces new real-world examples. Every chapter ends with a section of problems, as well as with an extended chapter project which often involves substantial computing work either in spreadsheet software or in the R statistical package.
From a widely published, international expert in both the theory and practical applications of the entity-relationship approach, this reference takes the reader from data entity analysis at the enterprise level...
The book will also be useful for professionals dealing with subsurface flow problems in hydrogeology, geologic carbon sequestration, and nuclear waste disposal.
This text teaches engineering and applied science students to incorporate empirical investigation into such design processes.
Stationary state space models for longitudinal data, Research Report #9, Department of Statistics, University of Southern Denmark. Jørgensen, B., Lundbye-Christensen, S., Song, P. X.-K. and Sun, L. (1996a).
This volume uses numerous solved examples, published case studies from the author’s own research, and well-conceived problems in order to enhance comprehension levels among readers and their understanding of the “processes”along with ...
This book introduces numerical methods for processing datasets which may be of any form, illustrating adequately computational resolution of environmental alongside the use of open source libraries.
After introducing the theory, the book covers the analysis of contingency tables, t-tests, ANOVAs and regression. Bayesian statistics are covered at the end of the book.
This book reviews some of today’s more complex problems, and reflects some of the important research directions in the field.
... Johnson in 1966 as referenced by Johnson (2000) and had actually been viewed by several authors as a reason not to use the CAR scores. For instance, Johnson (2000) explained that these decorrelated variables Z are only approximation of ...
This book is written for the students and practitioners who are looking for a single introductory Excel-based resource that covers three essential business and analytical skills—Data Analysis, Business Modeling, and Simulation of Complex ...