Regression Analysis

The origin of the term "regression" dates from Francis Galton's work with sweet pea seeds, and Karl Pearson's biography of Galton. At the Institute for Statistics Education, "Regression Analysis" is your bridge between introductory level courses and more advanced courses.

Dr. Iain Pardoe will present his course "Regression Analysis," online at statistics.com. "Regression Analysis" covers simple and multiple linear regression, standard assumptions and how to check them, what to do when they are not appropriate, diagnostics for residuals and influential observations, transformations, multicollinearity, auto-correlation, variable selection and more. For more details please visit at http://www.statistics.com/regression/.

Who Should Take This Course:

Scientists, business analysts, engineers and researchers who need to model relationships in data in which a single response variable depends on multiple predictor variables.

Course Program:

Course outline: The course is structured as follows

SESSION 1: Foundations and Simple Linear Regression

• Brief review of univariate statistical ideas:
• confidence intervals
• hypothesis testing
• prediction
• Simple linear regression model and least squares estimation
• Model evaluation:
• regression standard error
• R-squared
• testing the slope
• Checking model assumptions
• Estimation and prediction

SESSION 2: Multiple Linear Regression

• Multiple linear regression model and least squares estimation
• Model evaluation:
• regression standard error
• R-squared
• testing the regression parameters globally
• testing the regression parameters in subsets
• testing the regression parameters individually
• Checking model assumptions
• Estimation and prediction

SESSION 3: Model Building I

• Predictor transformations
• Response transformations
• Predictor interactions
• Qualitative predictors and the use of indicator variables

SESSION 4: Model Building II

• Influential points (outliers and leverage)
• Autocorrelation
• Multicollinearity
• Excluding important predictors
• Overfitting
• Extrapolation
• Missing data
• Model building guidelines
• Model interpretation using graphics

The instructor, Iain Pardoe, is the author of "Applied Regression Modeling: A Business Approach" (Wiley). If you are following the Oscars, check out his paper in the Journal of the Royal Statistical Society on predicting Academy Award winners. (http://www.iainpardoe.com/oscars.htm)

This course takes place over the internet at the Institute for 4 weeks. During each course week, you participate at times of your own choosing - there are no set times when you must be online. The course typically requires 15 hours per week. Course participants will be given access to a private discussion board so that they will be able to ask questions and exchange comments with instructor, Dr. Iain Pardoe. The class discussions led by the instructor, you can post questions, seek clarification, and interact with your fellow students and the instructor.

For Indian participants statistics.com accepts registration for its courses at special prices in Indian Rupees through its partner, the Center for eLearning and Training (C-eLT), Pune.

For India Registration and pricing, please visit us at www.india.statistics.com.

Email: info@c-elt.com

Call: 020 66009116

Websites:

www.india.statistics.com

www.c-elt.com