Population Health: Responsible Data Analysis
- 4.6
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Course Summary
This course teaches responsible data analysis and the ethical considerations that go with it. Students will learn how to collect, analyze, and use data in a way that respects privacy and human rights.Key Learning Points
- Learn the importance of responsible data analysis in today's world
- Understand the ethical considerations and legal requirements for handling data
- Develop skills in collecting, analyzing, and using data in a responsible manner
Related Topics for further study
Learning Outcomes
- Understand the ethical considerations of data analysis
- Develop skills in data collection and analysis
- Learn how to use data in a responsible and ethical manner
Prerequisites or good to have knowledge before taking this course
- Basic knowledge of statistics
- Familiarity with data analysis tools
Course Difficulty Level
IntermediateCourse Format
- Online
- Self-paced
Similar Courses
- Data Privacy and Security
- Ethics in Data Science
Related Education Paths
Related Books
Description
In most areas of health, data is being used to make important decisions. As a health population manager, you will have the opportunity to use data to answer interesting questions. In this course, we will discuss data analysis from a responsible perspective, which will help you to extract useful information from data and enlarge your knowledge about specific aspects of interest of the population.
Knowledge
- Knows (the value of) all aspects of data management and acknowledge the importance of initial data analysis.
- Knows the pros and cons of statistical methods and can choose the appropriate data analysis approach in common health related problems.
- Is able to interpret statistical results and to draw responsible conclusions.
Outline
- Welcome to Responsible Data Analysis
- Population health: Responsible Data Analysis
- How to succeed in your online class?
- Meet the instructors & the team
- Leiden University: Facts & Figures
- About this Course
- Glossary
- Community Guidelines
- What is your learning path?
- From Individuals to Data
- Introduction
- Structured data collection
- Data privacy and security
- Data description
- Initial data analysis
- To conclude
- Structured data collection in practice
- Privacy and security in practice
- Case Study: Descriptive Statistics
- Case study: Initial data analysis in practice
- Practice quiz
- Practice Quiz
- R exercise
- R exercise: Initial data analysis
- Reflect on your goals
- Test your knowledge
- From data to information I: statistical inference
- Introduction
- Statistical Inference
- Fundamentals of hypothesis testing
- Choosing the right statistical test
- Sample size calculation
- To conclude
- Confidence intervals in practice
- Relation between p-values and confidence intervals
- Hypothesis testing in practice
- Case study: Sample size calculation in practice
- Practice quiz statistical interference
- Practice quiz hypothesis testing
- Practice quiz: Which test?
- Practice quiz: Sample size
- Reflect on your goals
- Test your knowledge
- From data to information II: regression techniques
- Introduction
- Simple linear regression
- Multiple linear regression
- Logistic regression
- Cox proportional hazards regression
- To conclude
- Case study: Simple linear regression in practice
- Case study: Multiple linear regression in practice
- Case study: Logistic regression in practice
- Case study: Cox proportional hazards regression in practice
- R - exercise: Simple linear regression
- R exercise: Multiple linear regression
- R exercise: Logistic regression
- R-exercise: Cox proportional hazards regression
- Reflect on your goals
- Test your knowledge
- From information to knowledge
- Introduction
- Are most research findings false?
- Interview
- Data alone does not tell the whole story
- Good statistical practice
- To conclude
- Course Conclusion
- The Likelihood of Irreproducible Research
- Abandoning p-values?
- Understanding Simpson's paradox
- Why do we need to plan ahead?
- Practice quiz
- Reflect on your goals
- Test your knowledge
- Final assessment
Summary of User Reviews
Discover Responsible Data Analysis with this online course on Coursera. Students have rated this course highly for its comprehensive coverage of the topic and practical approach. One key aspect that many users thought was good is the interactive assignments.Pros from User Reviews
- Comprehensive coverage of responsible data analysis
- Practical approach to learning
- Interactive assignments
- Engaging and knowledgeable instructors
- Flexible schedule
Cons from User Reviews
- Limited interactivity with instructors
- Some technical issues with the platform
- Not suitable for advanced learners
- Lack of real-world examples
- Lengthy lectures
Mar Rodriguez Girondo
4.6 Raiting
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