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Regression Models

Course Summary

Learn how to use regression models, the most important statistical analysis tool in the data scientist's toolkit. This is the seventh course in the Johns Hopkins Data Science Specialization.


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    Course Syllabus

    In this course students will learn how to fit regression models, how to interpret coefficients, how to investigate residuals and variability.  Students will further learn special cases of regression models including use of dummy variables and multivariable adjustment. Extensions to generalized linear models, especially considering Poisson and logistic regression will be reviewed.

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    Recommended Background

    R programming, mathematical aptitude. The content in the  R Programming and Statistical Inference courses covers the necessary background. The material from Statistical inference could be taken concurrently with this class.

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    Course Format

    Weekly lecture videos and quizzes and a final peer-assessed project.


Course Fee:
Free

Course Type:

Self-Study

Course Status:

Active

Workload:

1 - 4 hours / week

This course is listed under Data & Information Management Community

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