This remarkably engaging textbook is the perfect learning resource for undergraduate and postgraduate biology students studying statistics and data analysis. Part of the best-selling Moore family of statistics books, it covers essential statistical topics with examples and exercises drawn from across the field of life sciences, including disciplines such as nursing, public health, and allied health. Based on David Moore's classic The Basic Practice of Statistics, this textbook applies the bestseller's signature emphasis on statistical thinking, real data and what statisticians actually do, to the world of life sciences, helping engage students and underlining how statistics can directly apply to the projects they're working on. The new edition includes new and updated exercises, examples, and samples of real data, as well as an expanded range of media tools for students and instructors. This textbook is also available on LaunchPad.
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This remarkably engaging text gives biology students an introduction to statistics. Based on a growing interest in statistics across the life science fields, The Practice of Statistics in the Life Sciences was developed from David Moore's The Basic Practice of Statistics and emphasizes statistical thinking and real data using up-to-date examples.
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1. Picturing Distributions with Graphs.- 2. Describing Distributions with Numbers.- 3. Scatterplots and Correlation.- 4. Regression.- 5. Two-Way Tables.- 6. Exploring Data: Part I Review.- 7. Samples and Observational Studies.- 8. Designing Experiments.- 9. Introducing Probability.- 10. General Rules of Probability.- 11. The Normal Distributions.- 12. Discrete Probability Distributions.- 13. Sampling Distributions.- 14. Introduction to Inference.- 15. Inference in Practice.- 16. From Exploration to Inference: Part II Review.- 17. Inference about a Population Mean.- 18. Comparing Two Means.- 19. Inference about a Population Proportion.- 20. Comparing Two Proportions.- 21. The Chi-Square Test for Goodness of Fit.- 22. The Chi-Square Test for Two-Way Tables.- 23. Inference for Regression.- 24. One-Way Analysis of Variance: Comparing Several Means.- 25. Inference: Part III Review.- Optional Companion Chapters (available at www.whfreeman.com/psls3e).- 26. More about Analysis of Variance: Follow-up Tests and Two-Way ANOVA.- 27. Nonparametric Tests.- 28. Multiple Regression.
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Produktdetaljer

ISBN
9781464175367
Publisert
2013-12-27
Utgave
3. utgave
Utgiver
Vendor
W.H.Freeman & Co Ltd
Høyde
260 mm
Bredde
220 mm
Aldersnivå
05, U
Språk
Product language
Engelsk
Format
Product format
Innbundet
Antall sider
608

Biographical note

Brigitte Baldi is a lecturer in the Department of Statistics at the University of California, Irvine. She was a local and later national advisor in the development of the statistics telecourse Statistically Speaking, and developed UCI's first online statistics courses.

David S. Moore is Shanti S. Gupta Distinguished Professor of Statistics, Emeritus, at Purdue University, USA, and was 1998 president of the American Statistical Association. He received his AB from Princeton and his PhD from Cornell, both in mathematics. He has written many research papers in statistical theory and served on the editorial boards of several major journals. Professor Moore is an elected fellow of the American Statistical Association and of the Institute of Mathematical Statistics and an elected member of the International Statistical Institute. He has served as program director for statistics and probability at the National Science Foundation. In recent years, Professor Moore has devoted his attention to the teaching of statistics. He was the content developer for the Annenberg/Corporation for Public Broadcasting college-level telecourse Against All Odds: Inside Statistics and for the series of video modules Statistics: Decisions through Data, intended to aid the teaching of statistics in schools. He is the author of influential articles on statistics education and of several leading texts. Professor Moore has served as president of the International Association for Statistical Education and has received the Mathematical Association of America's national award for distinguished college or university teaching of mathematics.