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    Read more about Natural Resources Biometrics

    Natural Resources Biometrics

    (2 reviews)

    Diane Kiernan, SUNY ESF

    Copyright Year:

    ISBN 13: 9781942341178

    Publisher: Open SUNY

    Language: English

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    Reviewed by L.K. Tuominen, Community Faculty, Metropolitan State University on 8/21/16

    This textbook provides appropriate coverage for an intermediate-level course in applied statistics. The first five chapters address content that would typically be covered in an introductory statistics course for students outside of mathematics,... read more

    Reviewed by Richard Harper, Asst. Professor, University of Massachusetts on 1/7/16

    This easy-to-read text covers the areas and principles of the subject appropriately and provides appropriately related lab/practical exercises. read more

    Table of Contents

    • Chapter 1: Descriptive Statistics and the Normal Distribution
    • Chapter 2: Sampling Distributions and Confidence Intervals
    • Chapter 3: Hypothesis Testing
    • Chapter 4: Inferences about the Differences of Two Populations
    • Chapter 5: One-way Analysis of Variance
    • Chapter 6: Two-way Analysis of Variance
    • Chapter 7: Correlation and Simple Linear Regression
    • Chapter 8: Multiple Linear Regression
    • Chapter 9: Modeling Growth, Yield, and Site Index
    • Chapter 10: Quantitative Measures of Diversity, Site Similarity, and Habitat Suitability

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    About the Book

    Natural Resources Biometrics begins with a review of descriptive statistics, estimation, and hypothesis testing. The following chapters cover one- and two-way analysis of variance (ANOVA), including multiple comparison methods and interaction assessment, with a strong emphasis on application and interpretation. Simple and multiple linear regressions in a natural resource setting are covered in the next chapters, focusing on correlation, model fitting, residual analysis, and confidence and prediction intervals. The final chapters cover growth and yield models, volume and biomass equations, site index curves, competition indices, importance values, and measures of species diversity, association, and community similarity.

    About the Contributors


    Diane Kiernan completed her Ph.D. in quantitative methods in forest science at SUNY ESF in 2007. She is currently teaching Introduction to Probability and Statistics and Forest Biometrics at SUNY ESF and Advanced Statistics at LeMoyne College in Syracuse, New York. She is employed as a biometrician analyzing long-term re-measurement data for the SUNY ESF forest properties and is involved with additional research projects at SUNY ESF. Diane has authored and co-authored two previous books on statistics currently being used in her classes.

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