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Elementary Statistics Concepts

Elementary Statistics Concepts
In this introduction, we will briefly discuss those elementary statistical concepts that provide the necessary foundations for more specialized expertise in any area of statistical data analysis. The selected topics illustrate the basic assumptions of most statistical methods and/or have been demonstrated in research to be necessary components of our general understanding of the "quantitative nature" of reality (Nisbett, et al., 1987). We will focus mostly on the functional aspects of the concepts discussed and the presentation will be very short. Further information on each of the concepts can be found in statistical textbooks. Recommended introductory textbooks are: Kachigan (1986), and Runyon and Haber (1976); for a more advanced discussion of elementary theory and assumptions of statistics, see the classic books by Hays (1988), and Kendall and Stuart (1979). What are Variables? Variables are things that we measure, control, or manipulate in research. Correlational vs. Dependent vs.

Against All Odds: Inside Statistics 1. What Is Statistics? Statistics is the art and science of gathering, organizing, analyzing and drawing conclusions from data. And without rudimentary knowledge of how it works, people can't make informed judgments and evaluations of a wide variety of things encountered in daily life. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19. 20. 21. 22. 23. 24. 25. 26. 27. 28. 29. 30. 31. 32.

HyperStat Online: An Introductory Statistics Textbook and Online Tutorial for Help in Statistics Courses Click here for more cartoons by Ben Shabad. Other Sources NIST/SEMATECH e-Handbook of Statistical Methods Stat Primer by Bud Gerstman of San Jose State University Statistical forecasting notes by Robert Nau of Duke University related: RegressIt Excel add-in by Robert Nau CADDIS Volume 4: Data Analysis (EPA) The little handbook of statistical practice by Gerard E. Stat Trek Tutorial Statistics at square 1 by T. Concepts and applications of inferential statistics by Richard Lowry of Vassar College CAST by W. SticiGui by P.