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Biological Statistics

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Biological Statistics

The goal in that class is to teach biology students how to choose the appropriate statistical test for a particular experiment, then apply that test and interpret the results. In my class and in this textbook, I spend relatively little time on the mathematical basis of the tests; for most biologists, statistics is just a useful tool, like a microscope, and knowing the detailed mathematical basis of a statistical test is as unimportant to most biologists as knowing which kinds of glass were used

Applied StatisticsStatistics
Author
John H. McDonald
Publisher
University of Delaware
Source
LibreTexts
Language
EN
Category
Basic Sciences
Read online Download PDF (open licence)
Contents· 52 sections
  1. 01: Basics
  2. 1.01: Data analysis steps
  3. 1.02: Types of Biological Variables
  4. 1.03: Probability
  5. 1.04: Basic Concepts of Hypothesis Testing
  6. 1.05: Confounding Variables
  7. 02: Tests for Nominal Variables
  8. 2.01: Exact Test of Goodness-of-Fit
  9. 2.02: Power Analysis
  10. 2.03: Chi-Square Test of Goodness-of-Fit
  11. 2.04: GTest of Goodness-of-Fit
  12. 2.05: Chi-square Test of Independence
  13. 2.06: GTest of Independence
  14. 2.07: Fisher's Exact Test
  15. 2.08: Small Numbers in Chi-Square and GTests
  16. 2.09: Repeated GTests of Goodness-of-Fit
  17. 2.10: Cochran-Mantel-Haenszel Test
  18. 03: Descriptive Statistics
  19. 3.01: Statistics of Central Tendency
  20. 3.02: Statistics of Dispersion
  21. 3.03: Standard Error of the Mean
  22. 3.04: Confidence Limits
  23. 04: Tests for One Measurement Variable
  24. 4.01: One-Sample t-Test
  25. 4.02: Two-Sample t-Test
  26. 4.03: Independence
  27. 4.04: Normality
  28. 4.05: Homoscedasticity and Heteroscedasticity
  29. 4.06: Data Transformations
  30. 4.07: One-way Anova
  31. 4.08: KruskalWallis Test
  32. 4.09: Nested Anova
  33. 4.10: Two-way Anova
  34. 4.11: Paired tTest
  35. 4.12: Wilcoxon Signed-Rank Test
  36. 05: Tests for Multiple Measurement Variables
  37. 5.01: Linear Regression and Correlation
  38. 5.02: Spearman Rank Correlation
  39. 5.03: Curvilinear (Nonlinear) Regression
  40. 5.04: Analysis of Covariance
  41. 5.05: Multiple Regression
  42. 5.06: Simple Logistic Regression
  43. 5.07: Multiple Logistic Regression
  44. 06: Multiple Tests
  45. 6.01: Multiple Comparisons
  46. 6.02: Meta-Analysis
  47. 07: Miscellany
  48. 7.01: Using Spreadsheets for Statistics
  49. 7.02: Guide to Fairly Good Graphs
  50. 7.03: Presenting Data in Tables
  51. 7.04: Introduction to SAS
  52. 7.05: Choosing the Right Test