Statistical analysis in microbiology : statnotes

Based on the highly successful STATNOTES articles published in Microbiologist by the Society for Applied Microbiology, this book presents the most useful statistical tests in a clear way by applying them to real experiments in microbiology, meeting the need for a book devoted to data analysis in the...

Full description

Bibliographic Details
Main Authors: Armstrong, Richard A. (Author), Hilton, Anthony C. (Author)
Format: Book
Language:English
Published: Hoboken, New Jersey : Wiley-Blackwell Publication , c2011
Subjects:
Table of Contents:
  • 1. Are the data normally distributed?
  • 2. Describing the normal distribution
  • 3. Testing the difference between two groups
  • 4. Wat if the data are not normally distributed?
  • 5. Chi-square contingency tables
  • 6. One-way analysis of variance (anova)
  • 7. Post hoc tests
  • 8. Is one set of data more variable than another?
  • 9. Statistical power and sample size
  • 10. One-way analysis of variance (random effects model) : the nested or hierarchical design
  • 11. Two-way analysis of variance
  • 12. Two-factor analysis of variance
  • 13. Split-plot analysis of variance
  • 14. Repeated-measures analysis of variance
  • 15. Correlation of two variables
  • 16. Limits of agreement
  • 17. Nonparametric correlation coefficients
  • 18. Fitting a regression line to data
  • 19. Using a regression line for prediction and calibration
  • 20. Comparison of regression lines
  • 21. Nonlinear regression : fitting an exponential curve
  • 22. Nonlinear regression : fitting a general polynomial-type curve
  • 23. Nonlinear regression : fitting a logistic growth curve
  • 24. Nonparametric analysis of variance
  • 25. Multiple linear regression
  • 26. Stepwise multiple regression
  • 27. Classification and dendrograms
  • 28. Factor analysis and principal components analysis
  • 29. Which test to use : table
  • 30. Which test to use : key
  • 31. Glossary of statistical terms and their abbreviations
  • 32. Summary of sample size procedures for different statistical tests