Statistical Research with SAS: Design, Analysis, Interpretation: Ready To Use

Name: Statistical Research with SAS: Design, Analysis, Interpretation: Ready To Use
Brand: Createspace Independent Publishing Platform
SKU: 9781453720813
Price: 1717.0 INR
Availability: InStock

by Zhi Li

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ISBN13: 9781453720813
Binding: Paperback
Subject: N/A
Publisher: Createspace Independent Publishing Platform
Publisher Imprint: Createspace Independent Publishing Platform
Publication Date: July 21, 2010
Pages: 108
Original Price: USD 20.0
Language: English
Edition: N/A
Item Weight: 155 grams
BISAC Subject(s): Applied Sciences

About The Book

This is an educational material book for college students to do statistical research by using SAS. SAS programming has been difficult for students, because Statistics students don't know how to write computer programs, and Computer Science students have no idea about statistical research. This book formulates 28 SAS programs for research; so that students don't need specialized programming skill to write their own codes. To use the programs of the book, students only need to follow the instructions from the book to design the statistical experiments, and use the students' data replaced the old data from the book. SAS can do the analysis by click of the button. This book also gives specific interpretation of each SAS output to help students understand their research results. 1. Histogram 2. Confidence interval 3. T-Test 4. Paired T Test 5. QQ Plot 6. T-Test with Two Treatment Groups 7. Wilcoxon Test 8. One-Way ANOVA 9. Two-Way ANOVA 10. Chi Square Test 11. Fisher Exact Test 12. Linear Regression 13. Kaplan Meier Survival Curve 14. Cochran-Mantel-Haenszel (CMH) test 15. Sample Size for Continuous Data 16. Power for Continuous Data 17. Minimal Relevant Difference for Continuous Data 18. Sample Size for Proportion 19. Power for Proportion 20. Minimal Relevant Difference for Proportion 21. Complete Randomization Allocation 22. Efron's Biased Coin Design 23. Truncated Binomial Randomization 24. Random Allocation Rule 25. Permuted Block Design 26. Linear Regression with Treatment Effect and Interaction 27. Logistic is Regression for Proportion 28. Proportional Hazards Model

About The Author

Current graduate student of Statistics from George Mason University United States Experienced Market Researcher BS of Bioinformatics from Auckland University New Zealand Member of Phi Delta Beta International Honor Society Member of American Statistician Association.

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