Linear Regression Modeling for Health Data (Coursera)

Linear Regression Modeling for Health Data (Coursera)
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There are no formal requirements to take this course. It is preferred that learners have a basic understanding of algebra and probability
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Linear Regression Modeling for Health Data (Coursera)
This course provides learners with a first look at the world of statistical modeling. It begins with a high-level overview of different philosophies on the question of 'what is a statistical model' and introduces learners to the core ideas of traditional statistical inference and reasoning. Learners will get their first look at the ever-popular t-test and delve further into linear regression. They will also learn how to fit and interpret regression models for a continuous outcome with multiple predictors.

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All concepts taught in this course will be covered with multiple modalities: slide-based lectures, guided coding practice with the instructor, and independent but structured exercises.

This course is part of the Data Science for Health Research Specialization.


What you'll learn

- Become knowledgeable about the concept of statistical modeling and the basics of statistical inference

- Recognize, fit, and interpret a simple linear regression model

- Develop intuition to fit and interpret a multiple regression model


Syllabus


Principles of Statistical Modeling

Module 1

This module gives you a first look at the world of statistical modeling. It begins with a high-level overview of different philosophies on the question of 'what is a statistical model' and introduces you to the core ideas of traditional statistical inference and reasoning. At the end of the module, you will have an introductory understanding of important terms such as 'sample-to-population' (STOP) principle, sampling variation, and measures of statistical uncertainty. You will also get your first look at the ever popular t-test.


Simple Linear Regression

Module 2

This module takes you beyond t-test into linear regression. By the end of the module, you will understand how linear regression is a generalization of the t-test.


Multiple Linear Regression

Module 3

A key reason that linear regression is so powerful is that it allows to adjust for multiple predictors at the same time. In Module 3, you will learn how to fit regression models for multiple predictors. You will see how to interpret the resulting model and how to use it to answer different questions about your data.



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

Course Auditing
45.00 EUR/month
There are no formal requirements to take this course. It is preferred that learners have a basic understanding of algebra and probability

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