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Education in Study Design and Statistics for Students and Professionals

Part of the Springer Series on Environmental Management book series (SSEM)

There is a fear of statistics among the public, state and federal officials, and even among numerous scientists. The general feeling appears to be based on the convoluted manner in which “statistics” is presented in the media and by the cursory introduction to statistics that most people receive in college. Among the media, we often hear that “statistics can be used to support anything you want”; thus, statistics (and perhaps statisticians by implication) become untrustworthy. Of course, nothing could be further from the truth. It is not statistics per se that is the culprit. Rather, it is usually the way in which the data were selected for analysis that results in skepticism among the public.

Additionally, and as we have emphasized throughout this book, “statistics” and “study design” are interrelated yet separate topics. No statistical analysis can repair data gathered from a fundamentally flawed design, yet improperly conducted statistical analyses can easily be corrected if the design was appropriate. In this chapter we outline the knowledge base we think all natural resource professionals should possess, categorized by the primary role one plays in the professional field. Students, scientists, managers, and yes, even administrators, must possess a fundamental understanding of study design and statistics if they are to make informed decisions. We hope that the guidance provided below will help steer many of you toward an enhanced understanding and appreciation of study design and statistics.

Keywords

Parametric Test Statistical Knowledge Basic Text Personal Opinion Resource Professional 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. Afifi, A. A. 2004. Computer-Aided Multivariate Analysis, 4th Edition. Chapman and Hall/CRC, Boca Raton, FL.Google Scholar
  2. Agresti, A. 1996. An Introduction to Categorical Data Analysis. Wiley, New York, NY.Google Scholar
  3. Agresti, A. 2002. Categorical Data Analysis, 2nd Edition. Wiley, New York, NY.Google Scholar
  4. Cochran, W. G. 1983. Planning and Analysis of Observational Studies. Wiley, New York, NY.CrossRefGoogle Scholar
  5. Conover, W. J. 1999. Practical Nonparametric Statistics, 3rd Edition. Wiley, New York, NY.Google Scholar
  6. Dillon, W. R., and M. Goldstein. 1984. Multivariate Analysis: Methods and Applications. Wiley, New York, NY.Google Scholar
  7. Draper, N. R., and H. Smith. 1998. Applied Regresion Analysis, 3rd Edition. Wiley, New York, NY.Google Scholar
  8. Fowler, J. L. Cohen, and P. Jarvis. 1998. Practical Statistics for Field Biology, 2nd Edition. Wiley, New York, NY.Google Scholar
  9. Garcia, M. W. 1989. Forest Service experience with interdisciplinary teams developing integrated resource management plans. Environ. Manage. 13: 583–592.CrossRefGoogle Scholar
  10. Hollander, M., and D. A. Wolfe. 1998. Nonparametric Statistical Methods, 2nd Edition. Wiley, New York, NY.Google Scholar
  11. Hoshmand, A. R. 2006. Design of Experiments for Agriculture and the Natural Sciences, 2nd Edition. Chapman and Hall/CRC, Boca Raton, FL.Google Scholar
  12. Hosmer Jr., D.W., and S. Lemeshow. 2000. Applied Logistic Regression, 2nd Edition. Wiley, New York, NY.Google Scholar
  13. Kish, L. 1987. Statistical Design for Research. Wiley, New York, NY.CrossRefGoogle Scholar
  14. Kish, L. 1995. Survey Sampling. Wiley, New York, NY (reprint of the 1965 edition).Google Scholar
  15. Kish, L. 2004. Statistical Design for Research. Wiley, New York, NY (reprint of the 1987 edition).Google Scholar
  16. Kleinbaum, D. G. 2005. Logistic Regression: A Self-Learning Text, 2nd Edition. Springer-Verlag, New York, NY.Google Scholar
  17. Le, C. T. 1998. Applied Categorical Data Analysis. Wiley, New York, NY.Google Scholar
  18. Levy, P. S., and S. Lemeshow. 1999. Sampling of Populations: Methods and Applications, 3rd Edition. Wiley, New York, NY.Google Scholar
  19. Manly, B. F. J. 1992. The Design and Analysis of Research Studies. Cambridge University Press, Cambridge.Google Scholar
  20. Manly, B. F. J. 2004. Multivariate Statistical Methods: A Primer, 3rd Edition. Chapman and Hall, Boca Raton, FL.Google Scholar
  21. Mood, A. M., F. A. Graybill, and D. C. Boes. 1974. Introduction to the Theory of Statistics, 3rd Edition. McGraw-Hill, Boston, MA.Google Scholar
  22. Morrison, M. L., and B. G. Marcot. 1995. An evaluation of resource inventory and monitoring program used in national forest planning. Environ. Manage. 19: 147–156.CrossRefGoogle Scholar
  23. Morrison, M. L., B. G. Marcot, and R. W. Mannan. 2006. Wildlife Habitat Relationships: Concepts and Applications, 3rd Edition. Island Press, Washington, DC.Google Scholar
  24. Motulsky, H. 1995. Intuitive Biostatistics. Oxford University Press, New York, NY.Google Scholar
  25. Rosenbaum, P. R. 2002. Observational Studies, 2nd Edition. Springer-Verlag, New York, NY.Google Scholar
  26. Schreuder, H. T., T. G. Gregoire, and G. B. Wood. 1993. Sampling Methods for Multiresource Forest Inventory. Wiley, New York, NY.Google Scholar
  27. Sokal, R. R., and F. J. Rohlf. 1981. Biometry, 2nd Edition. Freeman, New York, NY.Google Scholar
  28. Sokal, R. R., and F. J. Rohlf. 1995. Biometry, 3rd Edition. Freeman, New York, NY.Google Scholar
  29. Stokes, M. E., C. S. Davis, and G. G. Koch. 2000. Categorical Data Analysis in the SAS System, 2nd Edition. SAS Publishing, Cary, NC.Google Scholar
  30. Thompson, S. K. 2002. Sampling, 2nd Edition, Wiley, New York, NY.Google Scholar
  31. Underwood, A. J. 1997. Experiments in Ecology. Cambridge University Press, Cambridge.Google Scholar
  32. Watt, T. A. 1998. Introductory Statistics for Biology Students, 2nd Edition. Chapman and Hall, Boca Raton, FL.Google Scholar
  33. Williams, B. K., J. D. Nichols, and M. J. Conroy. 2002. Analysis and Management of Animal Populations. Academic, San Diego, CA.Google Scholar
  34. Zar, J. H. 1998. Biostatistical Analysis, 4th Edition. Prentice-Hall, Englewood Cliffs, NJ.Google Scholar

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