Logistic Regression and Prediction for Health Data
$49
ENROLL NOWCourse Overview
What You'll Learn
- 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.
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.
Course FAQs
Is this an accredited online course?
Accreditation for 'Logistic Regression and Prediction for Health Data' is determined by the provider, University of Michigan. For online college courses or degree programs, we strongly recommend you verify the accreditation status directly on the provider's website to ensure it meets your requirements.
Can this course be used for continuing education credits?
Many of the courses listed on our platform are suitable for professional continuing education. However, acceptance for credit varies by state and licensing board. Please confirm with your board and {course.provider} that this specific course qualifies.
How do I enroll in this online school program?
To enroll, click the 'ENROLL NOW' button on this page. You will be taken to the official page for 'Logistic Regression and Prediction for Health Data' on the University of Michigan online class platform, where you can complete your registration.
