Lawrence J. Drew - Böcker

This is the candid and often colourful account of the personal experiences of a resource analyst; experiences that led to major contributions in the modelling and forecasting of petroleum discovery rates and of potential oil and gas supply. The author's approach is largely nontechnical. He relates the difficulties encountered in integrating geoscience, economics, and statistics, and stresses the value of critically examining data before formulating theories or building formal models.

""" This book has been written as a guide to the management and use of formulated feeds in intensive fish and shrimp culture. While its focus is on the use of commercially pro­ duced feeds in intensive production systems, it is anticipated that many of the practical issues covered will be of equal interest to those fish farmers who make their own feeds and to those who use formulated feeds in less intensive systems. Feeds and feeding are the major variable operating costs in intensive aquaculture and the book is primarily in­ tended to aid decision making by fish farm managers in areas of feeding policy. The dramatic increases in aquaculture production seen over the past 15 years have been made possible, in large part, by gains in our understanding of the food and feed­ ing requirements of key fish and shrimp species. A global aquaculture feeds industry has developed and a wide range of specialist feeds is now sold. The new options in feeds and feeding systems, which are becoming available, necessitate continual review by farmers of their feeding policies, where choices must be made as to appropriate feed types and feeding methods. While growth rates and feed conversion values are the prime factors of interest to farmers, other important issues, such as product qualiry and environmental impacts of farm effluents, are also directly related to feed management practices.

A comprehensive treatment of statistical applications for solving real-world environmental problems A host of complex problems face today's earth science community, such as evaluating the supply of remaining non-renewable energy resources, assessing the impact of people on the environment, understanding climate change, and managing the use of water. Proper collection and analysis of data using statistical techniques contributes significantly toward the solution of these problems. Statistics for Earth and Environmental Scientists presents important statistical concepts through data analytic tools and shows readers how to apply them to real-world problems.The authors present several different statistical approaches to the environmental sciences, including Bayesian and nonparametric methodologies. The book begins with an introduction to types of data, evaluation of data, modeling and estimation, random variation, and sampling—all of which are explored through case studies that use real data from earth science applications. Subsequent chapters focus on principles of modeling and the key methods and techniques for analyzing scientific data, including: Interval estimation and Methods for analyzinghypothesis testing of means time series data Spatial statistics Multivariate analysis Discrete distributions Experimental design Most statistical models are introduced by concept and application, given as equations, and then accompanied by heuristic justification rather than a formal proof. Data analysis, model building, and statistical inference are stressed throughout, and readers are encouraged to collect their own data to incorporate into the exercises at the end of each chapter. Most data sets, graphs, and analyses are computed using R, but can be worked with using any statistical computing software. A related website features additional data sets, answers to selected exercises, and R code for the book's examples.Statistics for Earth and Environmental Scientists is an excellent book for courses on quantitative methods in geology, geography, natural resources, and environmental sciences at the upper-undergraduate and graduate levels. It is also a valuable reference for earth scientists, geologists, hydrologists, and environmental statisticians who collect and analyze data in their everyday work.