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Logistic Regression and Prediction for Health Data

This course introduces learners to the analysis of binary/dichotomous outcomes. Learners will become familiar with fundamental tests for two-group comparisons...

By University of Michigan on Coursera

About This Course

This course introduces learners to the analysis of binary/dichotomous outcomes. Learners will become familiar with fundamental tests for two-group comparisons and statistical inference plus prediction more broadly using logistic regression. They will understand the connection between prevalence, risk ratios, and odds ratios. By the end of this course, learners will be able to understand how binary outcomes arise, how to use R to compare proportions between two groups, how to fit logistic regressions in R, how to make predictions using logistic regression, and how to assess the quality of these predictions. 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.

Topics Covered

Frequently Asked Questions

How much does Logistic Regression and Prediction for Health Data cost?

Logistic Regression and Prediction for Health Data costs $49. Check the course page for current pricing and available discounts.

Who teaches Logistic Regression and Prediction for Health Data?

Logistic Regression and Prediction for Health Data is taught by University of Michigan, University of Michigan.

What skill level is Logistic Regression and Prediction for Health Data for?

This course is designed for all levels learners.

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$49.00
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Students0
DurationSelf-paced
LevelAll Levels
Languageen
PlatformCoursera