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| 100 |
1 |
|
|a Estabrook, George.
|
| 245 |
1 |
2 |
|a A Computational Approach to Statistical Arguments in Ecology and Evolution.
|
| 260 |
|
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|a Cambridge :
|b Cambridge University Press,
|c 2011.
|
| 300 |
|
|
|a 1 online resource (268 pages)
|
| 336 |
|
|
|a text
|b txt
|2 rdacontent
|
| 337 |
|
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|a computer
|b c
|2 rdamedia
|
| 338 |
|
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|a online resource
|b cr
|2 rdacarrier
|
| 505 |
0 |
|
|a Cover; Title; Copyright; Contents; Acknowledgments; 1 Introduction; 1.1 About the book; Purpose; Intended readers; Why use computation; Prerequisites; How to use this book; Brief overview; 1.2 Basic principles; Applicability; Argument style; Structure and variation; Example of a probability distribution; Other argument styles; 1.3 Scientific argument; Ingredients of statistical argument; Intellectual foundation; Structure; Test statistic; What is a statistical hypothesis?; Summary; 2 Programming and statistical concepts; 2.1 Computer programming; History; The two parts of a computer program.
|
| 505 |
8 |
|
|a PlacesService berry example; Instructions; Leading spaces; Spreadsheet I/O; Procedures; Errors; 2.2 You start programming; Experienced programmers; Getting started with EXCEL macro programming; How to read and write a spreadsheet from your macro; 2.3 Completing the service berry example; Fruit-ripening phenology; Mechanisms of variation in fruit-ripening date; The data; Hypothesis and statistic; A macro to calculate the predicted probability distribution; Calculate the test statistic; Remember the four ingredients; Name vs content; 2.4 Sub CARPEL; 2.5 You practice.
|
| 505 |
8 |
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|a More about the EXCEL macro editorA real exercise problem; How to solve it; Remember lawyers; 3 Choosing a test statistic; 3.1 Significance of what; Data from fossil marine organisms; The controversy; Relevance of precision; Two irrelevant statistics; Relevant statistics; Freedom to choose any statistic; 3.2 Implement the program; Hypotheses of non-periodicity; Computational overview; Sample the chosen hypothesis with computation; Calculate a relevant statistic; Discover inter-peak intervals; Testing the macro; Estimate realized significance; Using significance to argue; 3.3 Sub PERIOD.
|
| 505 |
8 |
|
|a 4 Random variables and distributions4.1 Random variables; At random; Random process; Continuous distributions; Random variable; 4.2 Distributions; Computation eliminates calculus; Bar graph; Practice writing a macro; Interpret the bar graph; Randomize; Accuracy vs precision; Pseudo-random; 4.3 Arithmetic with random variables; Hypotheses make statistics into random variables; Arithmetic with a random variable and numbers; A macro to convert u to another continuous uniform distribution; Sum of independent samples of the same binary random variable; Pascal's triangle; A macro to estimate s3.
|
| 505 |
8 |
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|a Macros to estimate other density distributions4.4 Expected value and variance; The middle of a distribution; Theoretical properties of expected value; Variance; Variance of the sum, f + g; The variance of u; 5 More programming and statistical concepts; 5.1 Re-sampling data; A question; Choose a test statistic; Design the macro; Not different mean same random process; Re-sampling data; Overview; Style; Efron; 5.2 Procedures; Why write procedures?; How to write a procedure; Access to places; Sub SORT; BIGDIF3; 5.3 Testing procedures; Testing SORT; Test data; Infinite loop; The watch window.
|
| 500 |
|
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|a Testing PERMUTE.
|
| 520 |
|
|
|a Teaches powerful methods to test hypotheses using statistical arguments without the constraints and sophisticated mathematics of classical statistics.
|
| 588 |
0 |
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|a Print version record.
|
| 504 |
|
|
|a Includes bibliographical references (pages 253-255) and index.
|
| 650 |
|
0 |
|a Ecology
|x Statistical methods
|x Data processing.
|
| 650 |
|
0 |
|a Ecology
|x Statistical methods.
|
| 650 |
|
0 |
|a Ecology.
|0 http://id.loc.gov/authorities/subjects/sh85040752
|
| 650 |
|
0 |
|a Evolution (Biology)
|x Statistical methods
|x Data processing.
|
| 650 |
|
0 |
|a Evolution (Biology)
|x Statistical methods.
|
| 650 |
|
0 |
|a Evolution.
|0 http://id.loc.gov/authorities/subjects/sh85046029
|
| 650 |
|
7 |
|a NATURE
|x Reference.
|2 bisacsh
|
| 650 |
|
7 |
|a SCIENCE
|x Life Sciences
|x Biology.
|2 bisacsh
|
| 650 |
|
7 |
|a SCIENCE
|x Life Sciences
|x General.
|2 bisacsh
|
| 650 |
|
7 |
|a Ecology.
|2 fast
|0 (OCoLC)fst00901476
|
| 650 |
|
7 |
|a Ecology
|x Statistical methods.
|2 fast
|0 (OCoLC)fst00901539
|
| 650 |
|
7 |
|a Evolution.
|2 fast
|0 (OCoLC)fst00917265
|
| 650 |
|
7 |
|a Evolution (Biology)
|x Statistical methods.
|2 fast
|0 (OCoLC)fst00917326
|
| 655 |
|
4 |
|a Electronic books.
|
| 776 |
0 |
8 |
|i Print version:
|a Estabrook, George.
|t A Computational Approach to Statistical Arguments in Ecology and Evolution.
|d Cambridge : Cambridge University Press, ©2011
|z 9781107004306
|
| 903 |
|
|
|a HeVa
|
| 929 |
|
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| 928 |
|
|
|t Library of Congress classification
|a QH371.3.S72 E88 2011
|l Online
|c UC-FullText
|u https://search.ebscohost.com/login.aspx?direct=true&scope=site&db=e000xna&AN=400628
|z eBooks on EBSCOhost
|g ebooks
|i 12359164
|
