Linear Regression on Demand

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Date/Time
Date(s) - 09/14/2020 - 10/12/2020
All Day

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For several years, Dr. Paul Allison has been presenting a 2-day, in-person seminar on Linear Regression at various locations around the US. Based on his book Multiple Regression, the course provides a very practical, intuitive, and non-mathematical introduction to the topic of linear regression.

This course takes place from September 14 to October 12, 2020 in a series of four weekly installments of videos, quizzes, readings, and assignments, and requires about 6-8 hours/week. You can participate at your own convenience; there are no set times when you are required to be online. The course can be accessed with any recent web browser on almost any platform, including iPhone, iPad, and Android devices. It consists of 10 modules:

– Introduction to Linear Regression
– Trivariate Regression
– Statistical Inference in Regression
– Dummy Variables and Standardized Coefficients
– Non-linearity
– Interaction
– Heteroscedasticity and Multicollinearity
– Missing Data
– Maximum Likelihood and Multiple Imputation
– Model Building and Variable Selection

The modules contain videos of the live, 2-day version of the course in its entirety. Each module is followed by a short multiple-choice quiz to test your knowledge. There are also weekly exercises that ask you to apply what you’ve learned to a real data set. You may submit your work for review by Dr. Allison.

Each week, there are 2-3 assigned articles to read. There is also an online discussion forum where you can post questions or comments about any aspect of the course. All questions will be promptly answered by Dr. Allison.

Downloadable course materials include the following pdf files:

All slides displayed in the videos.
Exercises for each week.
Readings for each week.
Computer code for all exercises (in SAS, Stata, and R formats).
A certificate of completion.

The fee of $495 (USD) includes all course materials. All major credit cards are accepted.

For more information and to register, visit https://statisticalhorizons.com/linear-regression-on-demand.

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