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Logistic Regression and Prediction for Health Data
Coursera MOOC / Non-credit 0

Logistic Regression and Prediction for Health Data

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.

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83/100

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32/45
Who stands behind it
35/35
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16/20

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What you'll learn

  • understand how binary outcomes arise
  • use R to compare proportions between two groups
  • fit logistic regressions in R
  • make predictions using logistic regression
  • assess the quality of predictions
Data Analysis #data visualization #statistical inference #r programming #health data analysis #logistic regression #data prediction #binary outcomes #odds ratios #comparative analysis #risk ratios
$49.00

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