Alain F. Zuur, Elena N. Ieno, Graham M. Smith's Analysing Ecological Data (Statistics for Biology and PDF

By Alain F. Zuur, Elena N. Ieno, Graham M. Smith

ISBN-10: 0387459677

ISBN-13: 9780387459677

This ebook presents a realistic creation to analysing ecological information utilizing actual info units accrued as a part of postgraduate ecological reviews or learn projects.

The first a part of the e-book provides a mostly non-mathematical advent to info exploration, univariate equipment (including GAM and combined modelling techniques), multivariate research, time sequence research (e.g. universal tendencies) and spatial data. the second one half presents 17 case stories, mostly written including biologists who attended classes given by means of the 1st authors. The case experiences comprise themes starting from terrestrial ecology to marine biology. The case reports can be utilized as a template on your personal facts research; simply attempt to discover a case learn that fits your individual ecological questions and information constitution, and use this as place to begin for you personal research. facts from all case reports can be found from www.highstat.com. information on software program is equipped in bankruptcy 2.

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Additional info for Analysing Ecological Data (Statistics for Biology and Health)

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PC-ORD is a Windows programme that performs multivariate analysis of ecological data entered into spreadsheets. Its emphasis is on non-parametric tools, graphical representation, and randomization tests for analysis of community data. In addition to utilities for transforming data and managing files, PC-ORD offers many ordination and classification techniques not available in other major statistical packages. Very large datasets can be analyzed. Most operations accept a matrix up to 32,000 rows or 32,000 columns and up to 536,848,900 matrix elements, provided that you have adequate memory in your machine.

2. Are there outliers? 3. Are the variables normally distributed? 4. Are there any relationships between the variables? Are relationships between the variables linear? Which follow-up analysis should be applied? 5. Do we need a transformation? 6. Was the sampling effort approximately the same for each observation or variable? We need to address all of these questions because the next step of the analysis needs the data to comply with several assumptions before any conclusions can be considered valid.

Org). This gives users a GUI alternative to the R command line interface, and with three exceptions allows all the techniques used in the book to be run from a single programme. The exceptions are (i) the geometric morphometries analysis of the landmark turtle data in Chapter 30, (ii) neural networks in Chapter 25, and (iii) kriging in Chapters 19 and 37. In these cases, we used specialised R routines. SPLUSandR Another programme we use extensively is SPLUS (http://www, insightful, com). SPLUS is a commercial implementation of the S language, which provides a userfriendly menu-driven interface.

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Analysing Ecological Data (Statistics for Biology and Health) by Alain F. Zuur, Elena N. Ieno, Graham M. Smith


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