John Hopkins University - Simple Regression Analysis in Public Health
- Offered byCoursera
Simple Regression Analysis in Public Health at Coursera Overview
Duration | 14 hours |
Start from | Start Now |
Total fee | Free |
Mode of learning | Online |
Difficulty level | Beginner |
Official Website | Explore Free Course |
Credential | Certificate |
Simple Regression Analysis in Public Health at Coursera Highlights
- This Course Plus the Full Specialization.
- Shareable Certificates.
- Graded Programming Assignments.
Simple Regression Analysis in Public Health at Coursera Course details
- 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 at Coursera Curriculum
Simple Regression Methods
Introduction
Simple Regression: An Overview
Simple Linear Regression with a Binary (or Nominal Categorical) Predictor
Simple Linear Regression with a Categorical Predictor
Simple Linear Regression with a Continuous Predictor
Simple Linear Regression Model: Estimating the Regression Equation?Accounting for Uncertainty in the Estimates
Measuring the Strength of a Linear Association
Additional Examples
Solutions to Linear Regression Practice Quiz
Quiz 1 Solution
Practice Quiz: Simple Linear Regression
Simple Linear Regression
Introduction
Simple Logistic Regression: An Overview
Simple Logistic Regression with a Binary (or Categorical) Predictor
Simple Logistic Regression with a Continuous Predictor
Simple Logistic Regression: Accounting for Uncertainty in the Estimates
Estimating Risk and Functions of Risk from Logistic Regression Results
Additional Examples
Solutions to Practice Quiz on Simple Logistic Regression
Quiz 2 Solutions
Practice Quiz: Simple Logistic Regression
Logistic Regression
Simple Cox Proportional Hazards Regression
Introduction
Simple Cox Regression: An Overview
Simple Cox Regression with a Binary (or Categorical) Predictor
Simple Cox Regression with a Continuous Predictor
Simple Cox Regression: Accounting for Uncertainty in the Estimates
Estimating Survival Curves from Cox Regression Results
Additional Examples
Solutions for Practice Quiz on Simple Cox Regression
Solutions to Summative Quiz 3
Practice Quiz: Simple Cox Proportional Hazards Regression
Simple Cox Regression
Confounding, Adjustment, and Effect Modification
Introduction
Confounding: A Formal Definition and Some Examples
Adjusted Estimates: Presentation, Interpretation, and Utility for Assessing Confounding
Adjusted Estimates: The General Idea Behind the Computations
Additional Examples
Effect modification: Introduction with an analytic example
Effect modification: Tree damage and elevation example
Effect modification: Examples from the literature
Confounding versus effect modification: A review
Additional examples
Solutions to Summative Quiz 4
Practice Quiz: Confounding and Effect Modification
Confounding and Effect Modification
Course Project
Biostatistical Consulting Project
Course Project Quiz
Simple Regression Analysis in Public Health at Coursera Admission Process
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