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Titlebook: Analyzing Ecological Data; Alain F. Zuur,Elena N. Ieno,Graham M. Smith Book 2007 The Editor(s) (if applicable) and The Author(s), under ex

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期刊全称Analyzing Ecological Data
影响因子2023Alain F. Zuur,Elena N. Ieno,Graham M. Smith
视频video
发行地址A comprehensive and practical guide to analysing ecological data based on courses given to researchers, environmental consultants and post graduate students..Provides comprehensive introductory chapte
学科分类Statistics for Biology and Health
图书封面Titlebook: Analyzing Ecological Data;  Alain F. Zuur,Elena N. Ieno,Graham M. Smith Book 2007 The Editor(s) (if applicable) and The Author(s), under ex
影响因子‘Which test should I apply?‘ During the many years of working with ecologists, biologists and other environmental scientists, this is probably the question that the authors of this book hear the most often. The answer is always the same and along the lines of ‘What are your underlying questions?‘, ‘What do you want to show?‘. The answers to these questions provide the starting point for a detailed discussion on the ecological background and purpose of the study. This then gives the basis for deciding on the most appropriate analytical approach. Therefore, a better start­ ing point for an ecologist is to avoid the phrase ‘test‘ and think in terms of ‘analy­ sis‘. A test refers to something simple and unified that gives a clear answer in the form of a p-value: something rarely appropriate for ecological data. In practice, one has to apply a data exploration, check assumptions, validate the models, per­ haps apply a series of methods, and most importantly, interpret the results in terms of the underlying ecology and the ecological questions being investigated. Ecology is a quantitative science trying to answer difficult questions about the complex world we live in. Most ecologists are
Pindex Book 2007
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https://doi.org/10.1057/9781137405579t takes into account auto-orrelation structures in the data. We also discuss a standard time series method, namely auto-regressive integrated moving average models with exogenous variables (ARIMAX). In Chapter 17, more specialised methods to estimate common trends are introduced.
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Advice for teachers,ence analysis, canonical correspondence analysis, redundancy analysis) and time series. Although these’ show-me-all’ courses were popular, the actual amount of information that participants were able to fully understand was far less than we had hoped for. It was just too much information for five da
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1431-8776 raduate students..Provides comprehensive introductory chapte‘Which test should I apply?‘ During the many years of working with ecologists, biologists and other environmental scientists, this is probably the question that the authors of this book hear the most often. The answer is always the same and
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Anwendung von Robotic Process Automation,el of ‘familiarity with basic statistics’. This is a very loose phrase, but you should feel reasonably comfortable with concepts such as normal distribution, p-value, correlation, regression and hypothesis testing. Any first-year university undergraduate statistics module should have covered these topics to the depth required.
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Stella Gatziu Grivas,Manuela Grafithout explanatory variables, whereas canonical correspondence analysis (CCA) and redundancy analysis (RDA) use both response and explanatory variables. In this chapter, we present PCA and RDA, and in the next chapter CA and CCA are discussed.
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