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
- Simple linear regression
- Linear testing and the meaning of regression
- Correlation in linear simple regression
- Parameter testing on correlation coefficient
- Regression with two random variables
- Regression parameter testing
- Multiple linear regression dummy variables
- Regression for categorical data
- Regression in matrices symbol
- Hypothesis testing and confidence interval
- Non linear simple regression
- Non linear multiple regression
- Multiple correlation and variable addition
- Partial correlation and variable control
- Auto correlation
- Auto correlation testing
- Standard error and independent data
- Transform selection
- Predictor selection for trial and error
- Predictor selection for schematic process models
- Regression and analysis of variance
- Two ways of ANOVA
- Factorial design and regression
- Interaction in regression
- Interaction in advanced regression
- Regression parameter testing
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