Lectures
- 1. Introduction and Collecting Data
- 2. Summarizing and Exploring Data
- 3. Summarizing and Exploring Data II
- 4. Review of Probability
- 5. Sampling Distributions
- 6. Basic Concepts of Inference
- 7. Inference for Single Samples
- 8. Inference for Two Samples
- 9. Inference for Proportion and Count Data
- 10. Inference in a Nutshell
- 11. Review and Examples
- 12. Simple Linear Regression and Correlation
- 13. Simple Linear Regression and Correlation II
- 14. Multiple Linear Regression
- 15. Logistic Regression
- 16. Regression Review and Robust Regression
- 17. ANOVA - single factor
- 18. ANOVA - multifactor
- 19. ANOVA - multifactor II
- 20. Nonparametric Methods
- 21. Nonparametric Methods II
Applied Statistics
Course Summary
This course is based on 15.075 Applied Statistics, Spring 2003 made available by Massachusetts Institute of Technology: MIT OpenCourseWare under the Creative Commons BY-NC-SA license.
This course is an introduction to applied statistics and data analysis. Topics include collecting and exploring data, basic inference, simple and multiple linear regression, analysis of variance, nonparametric methods, and statistical computing. It is not a course in mathematical statistics, but provides a balance between statistical theory and application. Prerequisites are calculus, probability, and linear algebra. It includes an excellent set of lecture slides.
Reading Material
1. Statistics and Data Analysis from Elementary to IntermediateTamhane, Ajit C., and Dorothy D. Dunlop. Statistics and Data Analysis from Elementary to Intermediate. Prentice Hall, 2000. (Click the image below for the link to the book)
2. Statistical Inference
Casella, George, and Roger L. Berger. Statistical Inference. Belmont, CA: Duxbury Press, 1990.
(Click the image below for the link to the 2001 edition)
3. Managerial Statistics
Albright, S. C., W. L. Winston, and C. J. Zappe. Managerial Statistics. Duxbury, 2000.
(Click the image below for the link to the 2001 edition)
