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Environmental data analysis with MatLab / William Menke and Joshua Menke.

By: Contributor(s): Material type: TextTextPublication details: Amsterdam : Elsevier/AP, ©2016.Edition: 2nd edDescription: xvii, 321 pages : illustrations ; 24 cmISBN:
  • 9780128044889
Subject(s): DDC classification:
  • 363.70015118 23 M545
Contents:
1. Data analysis with MatLab -- 2. A first look at data -- 3. Probability and what it has to do with data analysis -- 4. The power of linear models -- 5. Quantifying preconceptions -- 6. Detecting periodicities -- 7. The past influences the present -- 8. Patterns suggested by data -- 9. Detecting correlations among data -- 10.Filling in missing data -- 11. "Approximate" is not a pejorative word -- 12. Are my results significant? -- 13. Notes.
Summary: This new edition, though written in a self-contained way, is supplemented with data and MATLABïŽ scripts that can be used as a data analysis tutorial. New features include boxed crib sheets to help identify major results and important formulas and give brief advice on how and when they should be used. Numerical derivatives and integrals are derived and illustrated. Includes 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 coverage of cluster analysis and approximation techniques that are widely applied in data analysis, including Taylor Series and low-order polynomial approximations; non-linear least-squares with Newton's method;and pre-calculation and updating techniques applicable to real time data acquisition.
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Holdings
Item type Current library Call number Status Date due Barcode Item holds
Books ISI Library, Kolkata 363.70015118 M545 (Browse shelf(Opens below)) Available 137851
Total holds: 0

Includes bibliographical references and index

1. Data analysis with MatLab --
2. A first look at data --
3. Probability and what it has to do with data analysis --
4. The power of linear models --
5. Quantifying preconceptions --
6. Detecting periodicities --
7. The past influences the present --
8. Patterns suggested by data --
9. Detecting correlations among data --
10.Filling in missing data --
11. "Approximate" is not a pejorative word --
12. Are my results significant? --
13. Notes.

This new edition, though written in a self-contained way, is supplemented with data and MATLABïŽ scripts that can be used as a data analysis tutorial. New features include boxed crib sheets to help identify major results and important formulas and give brief advice on how and when they should be used. Numerical derivatives and integrals are derived and illustrated. Includes 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 coverage of cluster analysis and approximation techniques that are widely applied in data analysis, including Taylor Series and low-order polynomial approximations; non-linear least-squares with Newton's method;and pre-calculation and updating techniques applicable to real time data acquisition.

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