
Understanding Statistical Concepts Using S-plus
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The book offers a rich insight into how probability has shaped statistical procedures in the behavioral sciences, as well as a brief history behind the creation of various statistics. Computational skills are kept to a minimum by including S-PLUS programs that run the exercises in the chapters. Students are not required to master the writing of S-PLUS programs, but explanations of how the programs work and program output are included in each chapter. S-PLUS is an advanced statistical package that has an extensive library of functions, which offer flexibility in writing customized routines.
The S-PLUS functions provide the capability of programming object and dialog windows, which are commonly used in Windows software applications. The S-PLUS program also contains pull-down menus for the statistical analysis of data.
A ZIP file containing programs that work in S-PLUS 6.2 for use with this book is available for download from http://www.psypress.com/resources/9780805836233.zip - please note that these scripts will only run in S-PLUS 6.2 and not later versions due to changes in the programming language syntax.
Reviews / Votes
"A particularly useful feature of each chapter is the summary, which, in a succinct fashion, lists the concepts to be mastered."-CHOICE
"With the inclusion of S-Plus script files, their book [Schumacker/Akers] is intended to help students understand the statistical concepts covered in the classroom and in the primary textbook, as well as to introduce them to the S-Plus statistical software".
-The American Statistician
"This book is a beginning statistics text that contains many S-Plus routines which have been supplied on an accompanying CD. The book is a potential vehicle for learning S-Plus by means of the hands-on approach of understanding the many existing routines."
-Journal of Mathematics Psychology
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Content
ACKNOWLEDGMENTS
PART I: INTRODUCTION AND STATISTICAL THEORY
1. Statistical Theory
2. Generating Random Numbers
3. Frequency Distributions
4. Stem and Leaf Plots
5. Population Distributions
6. Measures of Central Tendency
7. Measures of Dispersion
8. Sample Size Effects
9. Tchebysheff Inequality Theorem
10. Normal Bell-Shaped Curve
PART II: PROBABILITY AND PROBABILITY DISTRIBUTIONS
11. Probability
12. Joint Probability
13. Addition Law of Probability
14. Multiplication Law of Probability
15. Conditional Probability
16. Combinations and Permutations
PART III: MONTE CARLO AND STATISTICAL DISTRIBUTIONS
17. Binomial Distribution
18. Monte Carlo Simulation
19. Normal Distribution
20. t Distribution
21. Chi-square distribution
22. F Distribution
PART IV: SAMPLING AND INFERENCE
23. Sampling Distributions
24. Central Limit Theorem
25. Confidence Intervals
26. Hypothesis Testing
27. Type I Error
28. Type II Error
PART V: HYPOTHESIS TESTING IN RESEARCH
29. z test statistic for proportions
30. Chi-square test statistic
31. t Test for Mean Differences
32. Analysis of Variance
33. Correlation
34. Linear Regression
PART VI: REPLICABILITY OF FINDINGS
35. Cross Validation
36. Jackknife
37. Bootstrap
38. Meta-Analysis
39. Significance Testing vs. Practical Importance
GLOSSARY OF TERMS
ABOUT THE AUTHORS
APPENDIX
ANSWERS TO CHAPTER EXERCISES
AUTHOR INDEX
SUBJECT INDEX
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