Biostatistics is the application of statistical reasoning to the life sciences, and it's the key to unlocking the data gathered by researchers and the evidence presented in the scientific public health literature. In this course, we'll focus on the use of simple regression methods to determine the relationship between an outcome of interest and a single predictor via a linear equation. Along the way, you'll be introduced to a variety of methods, and you'll practice interpreting data and performing calculations on real data from published studies. Topics include logistic regression, confidence intervals, p-values, Cox regression, confounding, adjustment, and effect modification.
Simple Regression Analysis in Public Health
Simple Regression Analysis in Public Health
This course is part of Biostatistics in Public Health Specialization
Instructor: John McGready, PhD, MS
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4.7
(382 reviews)
Beginner level
Recommended experience
13 hours to complete
3 weeks at 4 hours a week
Flexible schedule
Learn at your own pace
What you'll learn
Practice simple regression methods to determine relationships between an outcome and a predictor
Recognize confounding in statistical analysis
Perform estimate adjustments
Skills you'll gain
Details to know
Shareable certificate
Add to your LinkedIn profile
Assessments
9 assignments
Taught in English
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This course is part of the Biostatistics in Public Health Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 5 modules in this course
Module one covers simple regression, the four different types of regression, commonalities between them, and simple linear aggression. Before completing the graded quiz, you can test your knowledge with the practice quiz.
What's included
8 videos2 readings2 assignments
Within module two, we will look at logistic regression, create confidence intervals, and estimate p-values. You will have the opportunity to test your knowledge in both a practice quiz and a graded quiz.
What's included
7 videos2 readings2 assignments
Module three focuses on Cox regression with different predictors. You will have the opportunity to test your knowledge first with the practice quiz and, then, with the graded quiz.
What's included
7 videos2 readings2 assignments
Within module four, you will look at confounding and adjustment, and unadjusted and adjusted association estimates. Additionally, you will learn about effect modification. Similar to previous modules, you will first take a practice quiz before completing the graded quiz.
What's included
10 videos1 reading2 assignments
During this module, you get the chance to demonstrate what you've learned by putting yourself in the shoes of biostatistical consultant on two different studies, one about self-administration of injectable contraception and one about medical appointment scheduling in Brazil. The two research teams have asked you to help them interpret previously published results in order to inform the planning of their own studies. If you've already taken other courses in this specialization, then this scenario will be familiar.
What's included
1 reading1 assignment
Instructor
Instructor ratings
4.7 (77 ratings)Offered by
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4.7
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Showing 3 of 382
SR
5
Reviewed on Dec 9, 2020
Complex analyses clearly explained, with an emphasis on interpretation rather than on mechanics. Excellent examples from published literature used throughout. Highly recommended!
KH
4
Reviewed on Oct 18, 2019
The course content was great. However, there was some technical problems.
PV
5
Reviewed on Sep 5, 2020
Such complex concepts explained with ease. The section on confounding requires more than one reading. Really enjoyed it.
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