Applied Logistic Regression (Coursera)

Applied Logistic Regression (Coursera)
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Students interested in this course should have background in introductory statistical methods.
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Applied Logistic Regression (Coursera)
This course provides theoretical and practical training on the increasingly popular logistic regression model, which has become the standard analytical method for use with a binary response variable.

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This Applied Logistic Regression course provides theoretical and practical training for epidemiologists, biostatisticians and professionals of related disciplines in statistical modeling with particular emphasis on logistic regression.

The increasingly popular logistic regression model has become the standard method for regression analysis of binary response data in the health sciences.

By the end of this course, students should:

- Master methods of statistical modeling when the response variable is binary.

- Be confident users of the Stata package for computing binary logistic regression models.

This is a hands-on, applied course where students will become proficient at using computer software to analyze data drawn primarily from the fields of medicine, epidemiology and public health.

There will be many practical examples and homework exercises in this class to help you learn. If you fully apply yourself in this course and complete all of the homework, you will have the opportunity to master various methods of statistical modeling and you will become a more confident user of the Stata* package for computing linear, polynomial and multiple regression.

*Access to Stata will be provided at no cost for the duration of this course.


Note: Enrollment for this course will close on Wednesday, May 13, 2015.



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Applied Logistic Regression



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MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Free Course
Students interested in this course should have background in introductory statistical methods.

MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.