The Analysis of Biological Data plus SaplingPlus Pack
Published on 23. June 2020
Book
Mixed media product
978-1-319-34170-1 (ISBN)
Description
Analysis of Biological Data provides students with a practical foundation of statistics for biology students. Every chapter has several biological or medical examples of key concepts, and each example is prefaced by a substantial description of the biological setting. The emphasis on real and interesting examples carries into the problem sets where students have dozens of practice problems based on real data.
The third edition features over 200 new examples and problems. These include new calculation practice problems, which guide the student step by step through the methods, and a greater number of examples and topics come from medical and human health research. Every chapter has been carefully edited for even greater clarity and ease of use. All the data sets, R scripts for all worked examples in the book, as well as many other teaching resources, are available to adopting instructors.
The third edition features over 200 new examples and problems. These include new calculation practice problems, which guide the student step by step through the methods, and a greater number of examples and topics come from medical and human health research. Every chapter has been carefully edited for even greater clarity and ease of use. All the data sets, R scripts for all worked examples in the book, as well as many other teaching resources, are available to adopting instructors.
More details
Edition
1st ed. 2020
Language
English
Place of publication
New York
United States
Publishing group
Macmillan Learning
Target group
Professional and scholarly
Illustrations
Approx. 125 p. Book + Access Card. 2 volume-set.
Dimensions
Height: 235 mm
Width: 155 mm
ISBN-13
978-1-319-34170-1 (9781319341701)
Copyright in bibliographic data and cover images is held by Nielsen Book Services Limited or by the publishers or by their respective licensors: all rights reserved.
Schweitzer Classification
Persons
Michael Whitlock is an evolutionary biologist and population geneticist. He is a professor of zoology at the University of British Columbia, where he has taught statistics to biology students since 1995. Whitlock is known for his work on the spatial structure of biological populations, genetic drift, and the genetics of adaptation. He has worked with fungus beetles, rhinos, and fruit flies; mathematical theory; and statistical genetics. He is a fellow of the American Academy of Arts and Sciences and a fellow of the American Association for the Advancement of Science. He is also the former editor-in-chief of The American Naturalist.
Dolph Schluter is a Professor and Canada Research Chair in the Zoology Department and Biodiversity Research Center at the University of British Columbia. He is known for his research on the ecology and evolution of Galapagos finches and threespine stickleback. He is a fellow of the Royal Societies of Canada and London and a foreign member of the Academy of Arts and Sciences.
Dolph Schluter is a Professor and Canada Research Chair in the Zoology Department and Biodiversity Research Center at the University of British Columbia. He is known for his research on the ecology and evolution of Galapagos finches and threespine stickleback. He is a fellow of the Royal Societies of Canada and London and a foreign member of the Academy of Arts and Sciences.
Content
PART 1 INTRODUCTION TO STATISTICS
1. Statistics and samples 1
INTERLEAF 1 Biology and the history of statistics 23
2. Displaying data 25
3. Describing data 65
4. Estimating with uncertainty 95
INTERLEAF 2 Pseudoreplication 115
5. Probability 117
6. Hypothesis testing 149
INTERLEAF 3 Why statistical significance is not the same
as biological importance 176
PART 2 PROPORTIONS AND FREQUENCIES
7. Analyzing proportions 179
INTERLEAF 4 Correlation does not require causation 201
8. Fitting probability models to frequency data 203
INTERLEAF 5 Making a plan 233
9. Contingency analysis: associations between
categorical variables 235
Review Problems 1 269
vii
WS2_Frontmatter_pi-xxxiv_v2.indd 7 13/07/16 11:55 AM
viii Contents in brief
PART 3 COMPARING NUMERICAL VALUES
10. The normal distribution 273
INTERLEAF 6 Controls in medical studies 301
11. Inference for a normal population 303
12. Comparing two means 327
INTERLEAF 7 Which test should I use? 366
13. Handling violations of assumptions 369
Review Problems 2 417
14. Designing experiments 423
INTERLEAF 8 Data dredging 456
15. Comparing means of more than two groups 459
INTERLEAF 9 Experimental and statistical mistakes 500
PART 4 REGRESSION AND CORRELATION
16. Correlation between numerical variables 503
INTERLEAF 10 Publication bias 535
17. Regression 539
INTERLEAF 11 Using species as data points 593
Review Problems 3 597
PART 5 MODERN STATISTICAL METHODS
18. Multiple explanatory variables 605
19. Computer-intensive methods 635
20. Likelihood 655
21. Meta-analysis: combining information from
multiple studies 681
1. Statistics and samples 1
INTERLEAF 1 Biology and the history of statistics 23
2. Displaying data 25
3. Describing data 65
4. Estimating with uncertainty 95
INTERLEAF 2 Pseudoreplication 115
5. Probability 117
6. Hypothesis testing 149
INTERLEAF 3 Why statistical significance is not the same
as biological importance 176
PART 2 PROPORTIONS AND FREQUENCIES
7. Analyzing proportions 179
INTERLEAF 4 Correlation does not require causation 201
8. Fitting probability models to frequency data 203
INTERLEAF 5 Making a plan 233
9. Contingency analysis: associations between
categorical variables 235
Review Problems 1 269
vii
WS2_Frontmatter_pi-xxxiv_v2.indd 7 13/07/16 11:55 AM
viii Contents in brief
PART 3 COMPARING NUMERICAL VALUES
10. The normal distribution 273
INTERLEAF 6 Controls in medical studies 301
11. Inference for a normal population 303
12. Comparing two means 327
INTERLEAF 7 Which test should I use? 366
13. Handling violations of assumptions 369
Review Problems 2 417
14. Designing experiments 423
INTERLEAF 8 Data dredging 456
15. Comparing means of more than two groups 459
INTERLEAF 9 Experimental and statistical mistakes 500
PART 4 REGRESSION AND CORRELATION
16. Correlation between numerical variables 503
INTERLEAF 10 Publication bias 535
17. Regression 539
INTERLEAF 11 Using species as data points 593
Review Problems 3 597
PART 5 MODERN STATISTICAL METHODS
18. Multiple explanatory variables 605
19. Computer-intensive methods 635
20. Likelihood 655
21. Meta-analysis: combining information from
multiple studies 681