Introductory probability and statistics : applications for forestry and natural sciences / Antal Kozak ... [et al.].

With interest growing in areas of forestry, conservation and other natural sciences, the need to organize and tabulate large amounts of forestry and natural science information has become a necessary skill. Previous attempts of applying statistical methods to these areas tend to be over-specialized and of limited use; an elementary text using methods, examples and exercises that are relevant to forestry and the natural sciences is long overdue. This book utilises basic descriptive statistics and probability, as well as commonly used statistical inferential tools to introduce topics that are commonplace in a forestry context such as hypothesis texting, design of experiments, sampling methods, nonparametric tests and statistical quality control. It also contains examples and exercises drawn from the fields of forestry, wood science, and conservation.

1: STATISTICS AND DATA: What do Numbers have to do with Trees?2: DESCRIPTIVE STATISTICS: Making Sense of Data3: PROBABILITY: The Foundation of Statistics4: RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS: Outcomes of Random Experiments5: SOME DISCRETE PROBABILITY DISTRIBUTIONS: Describing Data that is Counted6: CONTINUOUS DISTRIBUTIONS AND THE NORMAL DISTRIBUTION: Describing Data that is Measured7: SAMPLING DISTRIBUTIONS: The Foundation of Inference8: ESTIMATION: Determining the Value of Population Parameters9: TESTS OF HYPOTHESES: Making Claims about Population Parameters10: GOODNESS-OF-FIT AND TEST FOR INDEPENDENCE: Testing Distributions11: REGRESSION AND CORRELATION: Relationships between Variables12: ANALYSIS OF VARIANCE: Testing Differences between Several Means13: SAMPLING METHODS AND DESIGN OF EXPERIMENTS: Collecting Data14: NONPARAMETRIC TESTS: Testing when Distributions are Unknown15: QUALITY CONTROL: Statistics for Production and Processing1: STATISTICS AND DATA: What do Numbers have to do with Trees?2: DESCRIPTIVE STATISTICS: Making Sense of Data3: PROBABILITY: The Foundation of Statistics4: RANDOM VARIABLES AND PROBABILITY DISTRIBUTIONS: Outcomes of Random Experiments5: SOME DISCRETE PROBABILITY DISTRIBUTIONS: Describing Data that is Counted6: CONTINUOUS DISTRIBUTIONS AND THE NORMAL DISTRIBUTION: Describing Data that is Measured7: SAMPLING DISTRIBUTIONS: The Foundation of Inference8: ESTIMATION: Determining the Value of Population Parameters9: TESTS OF HYPOTHESES: Making Claims about Population Parameters10: GOODNESS-OF-FIT AND TEST FOR INDEPENDENCE: Testing Distributions11: REGRESSION AND CORRELATION: Relationships between Variables12: ANALYSIS OF VARIANCE: Testing Differences between Several Means13: SAMPLING METHODS AND DESIGN OF EXPERIMENTS: Collecting Data14: NONPARAMETRIC TESTS: Testing when Distributions are Unknown15: QUALITY CONTROL: Statistics for Production and Processing

Includes bibliographical references (p. 317-319) and index.