Natural Resources Biometrics

by Diane Kiernan

Read here Read at LibreTextsPDF

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.

Description from LibreTexts.

Publisher
SUNY College of Environmental Science and Forestry
Subjects
Statistics, Applied Statistics
Licence
CC BY-NC-SA 3.0, as LibreTexts states it. Non-commercial use only.
Who can read
Tweens profiles and older, judged from its title and subjects

Contents

LibreTexts writes equations in TeX, and here they show as TeX; the PDF has them typeset.

  1. Front Matter
  2. TitlePage
  3. InfoPage
  4. Table of Contents
  5. Licensing
  6. 1: Descriptive Statistics and the Normal Distribution
  7. 1.1: Descriptive Statistics
  8. 1.2: Probability Distribution
  9. 2: Sampling Distributions and Confidence Intervals
  10. 2.1: Sampling Distribution of the Sample Mean
  11. 2.2: Confidence Intervals
  12. 3: Hypothesis Testing
  13. 3.1: The Fundamentals of Hypothesis Testing
  14. 3.2: Hypothesis Test about the Population Mean when the Population Standard Deviation is Known
  15. 3.3: Hypothesis Test about the Population Mean when the Population Standard Deviation is Unknown
  16. 3.4: Hypothesis Test for a Population Proportion
  17. 3.5: Hypothesis Test about a Variance
  18. 3.6: Putting it all Together Using the Classical Method
  19. 4: Inferences about the Differences of Two Populations
  20. 4.1: Inferences about Two Means with Independent Samples (Assuming Unequal Variances)
  21. 4.2: Pooled Two-sampled t-test (Assuming Equal Variances)
  22. 4.3: Inferences about Two Means with Dependent Samples—Matched Pairs
  23. 4.4: Inferences about Two Population Proportions
  24. 4.5: F-Test for Comparing Two Population Variances
  25. 4.6: Summary
  26. 5: One-Way Analysis of Variance
  27. 5.1: Analysis of Variance
  28. 5.2: Multiple Comparisons
  29. 6: Two-way Analysis of Variance
  30. 6.1: Main Effects and Interaction Effect
  31. 6.2: Multiple Comparisons
  32. 6.3: Summary And Software Solution
  33. 7: Correlation and Simple Linear Regression
  34. 7.1: Correlation
  35. 7.2: Simple Linear Regression
  36. 7.3: Population Model
  37. 7.4: Software Solution
  38. 8: Multiple Linear Regression
  39. 8.1: Multiple Regressions
  40. 8.2: Software Solution
  41. 9: Modeling Growth, Yield, and Site Index
  42. 9.1: Growth and Yield Models
  43. 9.2: Site Index
  44. 9.3: Reference
  45. 10: Quantitative Measures of Diversity, Site Similarity, and Habitat Suitability
  46. 10.1: Introduction, Simpson’s Index and Shannon-Weiner Index
  47. 10.2: Rank Abundance Graphs and Habitat Suitability Index
  48. 10.3: Reference
  49. 11: Biometric Labs
  50. 11.1: Biometrics Lab #1
  51. 11.2: Biometrics Lab #2
  52. 11.3: Biometrics Lab #3
  53. 11.4: Biometrics Lab #4
  54. 11.5: Biometrics Lab #5
  55. Back Matter
  56. Index
  57. Glossary
  58. Glossary
  59. Detailed Licensing