Buch, Englisch, 480 Seiten, Format (B × H): 159 mm x 243 mm, Gewicht: 794 g
Buch, Englisch, 480 Seiten, Format (B × H): 159 mm x 243 mm, Gewicht: 794 g
Reihe: Chapman & Hall/CRC Texts in Statistical Science
ISBN: 978-1-58488-541-2
Verlag: Taylor & Francis Ltd
Modern computer-intensive statistical methods play a key role in solving many problems across a wide range of scientific disciplines. This new edition of the bestselling Randomization, Bootstrap and Monte Carlo Methods in Biology illustrates the value of a number of these methods with an emphasis on biological applications.
This textbook focuses on three related areas in computational statistics: randomization, bootstrapping, and Monte Carlo methods of inference. The author emphasizes the sampling approach within randomization testing and confidence intervals. Similar to randomization, the book shows how bootstrapping, or resampling, can be used for confidence intervals and tests of significance. It also explores how to use Monte Carlo methods to test hypotheses and construct confidence intervals.
New to the Third Edition
- Updated information on regression and time series analysis, multivariate methods, survival and growth data as well as software for computational statistics
- References that reflect recent developments in methodology and computing techniques
- Additional references on new applications of computer-intensive methods in biology
Providing comprehensive coverage of computer-intensive applications while also offering data sets online, Randomization, Bootstrap and Monte Carlo Methods in Biology, Third Edition supplies a solid foundation for the ever-expanding field of statistics and quantitative analysis in biology.
Zielgruppe
Undergraduate
Fachgebiete
Weitere Infos & Material
Randomization. The Jackknife. The Bootstrap. Monte Carlo Methods. Some General Considerations. One- and Two-Sample Tests. Analysis of Variance. Regression Analysis. Distance Matrices and Spatial Data. Other Analyses on Spatial Data. Time Series. Multivariate Data. Survival and Growth Data. Nonstandard Situations. Bayesian Methods. Final Comments. References. Appendix. Index.
