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E-raamat: Computational Approach to Statistical Arguments in Ecology and Evolution

(University of Michigan, Ann Arbor)
  • Formaat: PDF+DRM
  • Ilmumisaeg: 29-Sep-2011
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9781139119733
  • Formaat - PDF+DRM
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  • Formaat: PDF+DRM
  • Ilmumisaeg: 29-Sep-2011
  • Kirjastus: Cambridge University Press
  • Keel: eng
  • ISBN-13: 9781139119733

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Scientists need statistics. Increasingly this is accomplished using computational approaches. Freeing readers from the constraints, mysterious formulas and sophisticated mathematics of classical statistics, this book is ideal for researchers who want to take control of their own statistical arguments. It demonstrates how to use spreadsheet macros to calculate the probability distribution predicted for any statistic by any hypothesis. This enables readers to use anything that can be calculated (or observed) from their data as a test statistic and hypothesize any probabilistic mechanism that can generate data sets similar in structure to the one observed. A wide range of natural examples drawn from ecology, evolution, anthropology, palaeontology and related fields give valuable insights into the application of the described techniques, while complete example macros and useful procedures demonstrate the methods in action and provide starting points for readers to use or modify in their own research.

Ideal for researchers who want to take control of their own statistical arguments, this book teaches powerful computational methods to test hypotheses without the constraints and sophisticated mathematics of classical statistics. Examples of spreadsheet macros and real world applications are provided throughout to illustrate the concepts and techniques described.

Arvustused

'I recommend this volume to students and researchers looking for an easy, interesting, and condensed introduction to a computational approach to statistics.' The Quarterly Review of Botany

Muu info

This book teaches powerful methods to test hypotheses using statistical arguments without the constraints and sophisticated mathematics of classical statistics.
Acknowledgments vii
1 Introduction
1(19)
1.1 About the book
1(9)
1.2 Basic principles
10(4)
1.3 Scientific argument
14(6)
2 Programming and statistical concepts
20(39)
2.1 Computer programming
20(11)
2.2 You start programming
31(5)
2.3 Completing the service berry example
36(13)
2.4 Sub CARPEL
49(4)
2.5 You practice
53(6)
3 Choosing a test statistic
59(18)
3.1 Significance of what
59(4)
3.2 Implement the program
63(8)
3.3 Sub PERIOD
71(6)
4 Random variables and distributions
77(24)
4.1 Random variables
77(4)
4.2 Distributions
81(7)
4.3 Arithmetic with random variables
88(6)
4.4 Expected value and variance
94(7)
5 More programming and statistical concepts
101(21)
5.1 Re-sampling data
101(9)
5.2 Procedures
110(5)
5.3 Testing procedures
115(7)
6 Parametric distributions
122(19)
6.1 Basic concepts
122(2)
6.2 Poisson distribution
124(7)
6.3 Normal distribution
131(4)
6.4 Negative binomial, Chi Square, and F distributions
135(2)
6.5 Percentiles
137(4)
7 Linear model
141(28)
7.1 Linear model
141(1)
7.2 Quantifying error
142(3)
7.3 Linear model in matrix form
145(5)
7.4 Using a linear model
150(5)
7.5 Hypotheses of random for a linear model
155(5)
7.6 Two-way analysis of variance
160(9)
8 Fitting distributions
169(13)
8.1 Estimation of parameters
169(7)
8.2 Goodness of fit
176(6)
9 Dependencies
182(31)
9.1 Interpreting mixtures
182(5)
9.2 Series of dependent random variables
187(9)
9.3 Analysis of covariance
196(5)
9.4 Confounding dependencies
201(6)
9.5 Sub SEXDIMO
207(6)
10 How to get away with peeking at data
213(7)
11 Contingency
220(33)
11.1 What is contingency
220(3)
11.2 ACTUS2
223(18)
11.3 Spreadsheet ACTUS
241(3)
11.4 Sub ACTUS
244(9)
References 253(3)
Index 256
George Estabrook is a Professor of Botany in the Department of Ecology and Evolutionary Biology at the University of Michigan, Ann Arbor. He is interested in the application of mathematics and computing to biology and has taught graduate courses on the subject for more than 30 years.