Environmental Data Analysis With Matlab
  • Release Date : 15 March 2016
  • Publisher : Academic Press
  • Genre : Uncategorized
  • Pages : 342 pages
  • ISBN 13 : 0128044888
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Download or read book entitled Environmental Data Analysis With Matlab by author: William Menke which was release on 15 March 2016 and published by Academic Press with total page 342 pages . This book available in PDF, EPUB and Kindle Format. Since publication of the bestselling Environmental Data Analysis with MATLAB®, many advances have been made in environmental data analysis. This new edition expands fundamentally on the original with an expanded tutorial approach, with new crib sheets and problem sets providing a clear learning path for students and researchers working to analyze real data sets in the environmental sciences. One only has to consider the global warming debate to realize how critically important it is to be able to derive clear conclusions from often-noisy data drawn from a broad range of sources. The work teaches the basics of the underlying theory of data analysis and then reinforces that knowledge with carefully chosen, realistic scenarios. MATLAB®, a commercial data processing environment, is used in these scenarios; significant content is devoted to teaching how it can be effectively used in an environmental data analysis setting. This new edition, though written in a self-contained way, is supplemented with data and MATLAB® scripts that can be used as a data analysis tutorial. New to this edition: Throughout, boxed "crib sheets" help identify major results and important formulas and give brief advice on how and when they should be used Numerical derivatives and integrals derived and illustrated Expansion to include log-log plots with further examples of their use Discusses new datasets on precipitation and stream flow Topical enhancement applies the chi-squared test to the results of the generalized least squares method New section on cluster analysis New coverage of approximations techniques that are widely applied in data analysis. These include Taylor Series and low-order polynomial approximations; non-linear least-squares with Newton's method; pre-calculation and updating techniques applicable to real time data acquisition; and neural networks for approximating complex relationships Corrections of typographical errors and of call outs of figures and equations Provides a clear learning path for researchers and students using data analysis techniques which build upon one another, choosing the right order of presentation to substantially aid the reader learning material Crib Sheets serve to summarize the most important data analysis techniques, results, procedures and formulas, serving to organize the material in such a way that its sequence is more apparent Uses real-world environmental examples and case studies formulated using the readily-available software environment in MATLAB®