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Natural Resources Biometrics

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Natural Resources Biometrics

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.

Applied StatisticsStatistics
Author
Diane Kiernan
Publisher
SUNY College of Environmental Science and Forestry
Source
LibreTexts
License
CC BY-NC-SA
Language
EN
Category
Basic Sciences
Read online Download PDF (open licence)
Contents· 49 sections
  1. 01: Descriptive Statistics and the Normal Distribution
  2. 1.01: Descriptive Statistics
  3. 1.02: Probability Distribution
  4. 02: Sampling Distributions and Confidence Intervals
  5. 2.01: Sampling Distribution of the Sample Mean
  6. 2.02: Confidence Intervals
  7. 03: Hypothesis Testing
  8. 3.01: The Fundamentals of Hypothesis Testing
  9. 3.02: Hypothesis Test about the Population Mean when the Population Standard Deviation is Known
  10. 3.03: Hypothesis Test about the Population Mean when the Population Standard Deviation is Unknown
  11. 3.04: Hypothesis Test for a Population Proportion
  12. 3.05: Hypothesis Test about a Variance
  13. 3.06: Putting it all Together Using the Classical Method
  14. 04: Inferences about the Differences of Two Populations
  15. 4.01: Inferences about Two Means with Independent Samples (Assuming Unequal Variances)
  16. 4.02: Pooled Two-sampled t-test (Assuming Equal Variances)
  17. 4.03: Inferences about Two Means with Dependent SamplesMatched Pairs
  18. 4.04: Inferences about Two Population Proportions
  19. 4.05: F-Test for Comparing Two Population Variances
  20. 4.06: Summary
  21. 05: One-Way Analysis of Variance
  22. 5.01: Analysis of Variance
  23. 5.02: Multiple Comparisons
  24. 06: Two-way Analysis of Variance
  25. 6.01: Main Effects and Interaction Effect
  26. 6.02: Multiple Comparisons
  27. 6.03: Summary And Software Solution
  28. 07: Correlation and Simple Linear Regression
  29. 7.01: Correlation
  30. 7.02: Simple Linear Regression
  31. 7.03: Population Model
  32. 7.04: Software Solution
  33. 08: Multiple Linear Regression
  34. 8.01: Multiple Regressions
  35. 8.02: Software Solution
  36. 09: Modeling Growth Yield and Site Index
  37. 9.01: Growth and Yield Models
  38. 9.02: Site Index
  39. 9.03: Reference
  40. 10: Quantitative Measures of Diversity Site Similarity and Habitat Suitability
  41. 10.01: Introduction Simpsons Index and Shannon-Weiner Index
  42. 10.02: Rank Abundance Graphs and Habitat Suitability Index
  43. 10.03: Reference
  44. 11: Biometric Labs
  45. 11.01: Biometrics Lab 1
  46. 11.02: Biometrics Lab 2
  47. 11.03: Biometrics Lab 3
  48. 11.04: Biometrics Lab 4
  49. 11.05: Biometrics Lab 5