Statistics with Applications in Biology and Geology

Statistics with Applications in Biology and Geology

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The use of statistics is fundamental to many endeavors in biology and geology. For students and professionals in these fields, there is no better way to build a statistical background than to present the concepts and techniques in a context relevant to their interests. Statistics with Applications in Biology and Geology provides a practical introduction to using fundamental parametric statistical models frequently applied to data analysis in biology and geology. Based on material developed for an introductory statistics course and classroom tested for nearly 10 years, this treatment establishes a firm basis in models, the likelihood method, and numeracy. The models addressed include one sample, two samples, one- and two-way analysis of variance, and linear regression for normal data and similar models for binomial, multinomial, and Poisson data. Building on the familiarity developed with those models, the generalized linear models are introduced, making it possible for readers to handle fairly complicated models for both continuous and discrete data. Models for directional data are treated as well. The emphasis is on parametric models, but the book also includes a chapter on the most important nonparametric tests. This presentation incorporates the use of the SAS statistical software package, which authors use to illustrate all of the statistical tools described. However, to reinforce understanding of the basic concepts, calculations for the simplest models are also worked through by hand. SAS programs and the data used in the examples and exercises are available on the more

Product details

  • Paperback | 568 pages
  • 180.8 x 253.5 x 30mm | 984.3g
  • Taylor & Francis Inc
  • Chapman & Hall/CRC
  • Boca Raton, FL, United States
  • English
  • 95 black & white illustrations, 96 black & white tables
  • 158488309X
  • 9781584883098

Review quote

"The authors provide a useful website for the book [which] contains the many data sets used in the examples and exercises, as well as the SAS jobs. [T]his book could be a very good source of supplementary, applied material [or] an excellent book for a second course in practical applications." - Computers & Geosciences Promo Copyshow more

Table of contents

STATISTICAL ANALYSIS Data Model Specification Model Checking Statistical Inference Concluding Remarks PRELIMINARY INVESTIGATIONS Dot Diagrams and Bar Charts Histograms Fractile Diagrams Fractile Diagrams for the Normal Distribution Transformation Concluding Remarks Annex to Chapter 2 NORMAL DATA One Sample Annex to Section Main Points in Section Two or More Samples Main Points in Section Linear Regression Annex to Section Main Points in Section Supplement to Chapter The Normal Distribution and Related Distributions Multivariate Normal Distributions LINEAR NORMAL MODELS The Linear Normal Model Main Points in Section Comparison of Regression Lines Annex to Section Two-way Analysis of Variance Annex to Section 4 AN INTRODUCTION TO POWER OF TESTS AND DESIGN OF EXPERIMENTS Power of Tests Reduction of s 2- An Example of Blocking Control Plot for the Paired t-Test The Paired t--Test and Two-Way Analysis of Variance Annex to Chapter Supplement to Chapter 5 Non-Central t-, c, and F-Distributions CORRELATION Introduction Definitions Examples The Bivariate Normal Distribution Model Checking Inference on r Based on a Single Bivariate Normal Sample Inference on r Based on Several Bivariate Normal Samples Correlation and Regression Interpretation of Correlation Further Topics in the Bivariate Normal Distribution Annex to Chapter 6 Main Points in Section 6 THE MULTINOMIAL DISTRIBUTION Examples Inference in One Multinomial Distribution Inference in Several Multinomial Distributions Fisher's Exact Test Test for Goodness of Fit Sequence of Models Annex to Chapter 7 Main Points in Chapter 7 THE POISSON DISTRIBUTION Examples Probabilistic Results for the Poisson Distribution One Sample Several Samples Transformation Annex to Chapter 8 Main Points in Chapter 8 GENERALIZED LINEAR MODELS Classes of Distributions The Generalized Linear Model Examples MODELS FOR DIRECTIONAL DATA Notation Examples The Circular Normal Distribution One Sample Several Samples Annex to Chapter 10 Supplement to Chapter 10 Descriptive Measures for Directional Data Further Analogies THE LIKELIHOOD METHOD Likelihood Inference Concepts from General Test Theory Approximative Likelihood Theory SOME NONPARAMETRIC TESTS Sign Test Rank Tests Annex to Chapter 12 Main Points in Chapter 12 APPENDICES Simulated Fractile Diagrams The Newton-Raphson Procedure REFERENCES INDEXshow more