Regression Analysis

Learning Outcomes

At the end of this course, the students will be able to: Select regression prediction; Calculate parameter estimation for regression and correlation; Explain the connections between variables; Describe nonlinear simple and multiple regression equations

Topics

1. Simple linear regression
2. Linear testing and the meaning of regression
3. Correlation in linear simple regression
4. Parameter testing on correlation coefficient
5. Regression with two random variables
6. Regression parameter testing
7. Multiple linear regression dummy variables
8. Regression for categorical data
9. Regression in matrices symbol
10. Hypothesis testing and confidence interval
11. Non linear simple regression
12. Non linear multiple regression
13. Multiple correlation and variable addition
14. Partial correlation and variable control
15. Auto correlation
16. Auto correlation testing
17. Standard error and independent data
18. Transform selection
19. Predictor selection for trial and error
20. Predictor selection for schematic process models
21. Regression and analysis of variance
22. Two ways of ANOVA
23. Factorial design and regression
24. Interaction in regression
25. Interaction in advanced regression
26. Regression parameter testing