Description
Book SynopsisAll students, practitioners and researchers in forestry and related disciplines need a good grounding in statistics and probability. This need is increasing as techniques for gathering and analysing large amounts of data are becoming commonplace. This revised edition of this unique textbook is specifically designed for statistics and probability courses taught to students of forestry and related disciplines. It introduces probability, statistical techniques, data analysis, hypothesis testing, experimental design, sampling methods, nonparametric tests and statistical quality control, using examples drawn from a forestry, wood science and conservation context. The book now includes several new practical exercises for students to practice data analysis and experimental design themselves. It has been updated throughout, and its scope has been broadened to reflect the evolving and dynamic nature of forestry, bringing in examples from conservation science, recreation and urban forestry. - Specifically written and designed to teach statistics and probability to students of forestry and related disciplines in the natural sciences - This revised edition has been broadened to reflect the dynamism of modern forestry -Chapters in this revised edition include new practical exercises allowing students to practice data analysis and experimental design
Table of Contents1: STATISTICS AND DATA: What do Numbers have to do with Trees? 2: DESCRIPTIVE STATISTICS: Making Sense of Data 3: PROBABILITY: The Foundation of Statistics 4: RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS: Outcomes of Random Experiments 5: SOME DISCRETE PROBABILITY DISTRIBUTIONS: Describing Data that is Counted 6: CONTINUOUS DISTRIBUTIONS AND THE NORMAL DISTRIBUTION: Describing Data that is Measured 7: SAMPLING DISTRIBUTIONS: The Foundation of Inference 8: ESTIMATION: Determining the Value of Population Parameters 9: TESTS OF HYPOTHESES: Making Claims about Population Parameters 10: GOODNESS-OF-FIT AND TEST FOR INDEPENDENCE: Testing Distributions 11: REGRESSION AND CORRELATION: Relationships between Variables 12: ANALYSIS OF VARIANCE: Testing Differences between Several Means 13: SAMPLING METHODS AND DESIGN OF EXPERIMENTS: Collecting Data 14: NONPARAMETRIC TESTS: Testing when Distributions are Unknown 15: QUALITY CONTROL: Statistics for Production and Processing
