Causal Diagrams: Draw Your Assumptions Before Your Conclusions from edX

Causal diagrams have revolutionized the way in which researchers ask: What is the causal effect of X on Y? They have become a key tool for researchers who study the effects of treatments, exposures, and policies. By summarizing and communicating assumptions about the causal structure of a problem, causal diagrams have helped clarify apparent paradoxes, describe common biases, and identify adjustment variables. As a result, a sound understanding of causal diagrams is becoming increasingly important in many scientific disciplines.

The first part of this course is comprised of seven lessons that introduce causal diagrams and its applications to causal inference. The first lesson introduces causal DAGs, a type of causal diagrams, and the rules that govern them. The second, third, and fourth lessons use causal DAGs to represent common forms of bias. The fifth lesson uses causal DAGs to represent time-varying treatments and treatment-confounder feedback, as well as the bias of conventional statistical methods for confounding adjustment. The sixth lesson introduces SWIGs, another type of causal diagrams. The seventh lesson guides learners in constructing causal diagrams.

The second part of the course presents a series of case studies that highlight the practical applications of causal diagrams to real-world questions from the health and social sciences.

Professor Photo Credit: Anders Ahlbom

What's inside

Learning objectives

How to translate expert knowledge into a causal diagram
How to draw causal diagrams under different assumptions

Using causal diagrams to identify common biases
Using causal diagrams to guide data analysis

How to translate expert knowledge into a causal diagram
How to draw causal diagrams under different assumptions
Using causal diagrams to identify common biases
Using causal diagrams to guide data analysis

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Introduces causal diagrams, a powerful tool for researchers studying the causal effects of treatments, exposures, and policies

Provides a solid understanding of causal diagrams, which is becoming increasingly important in many scientific disciplines

Develops skills in translating expert knowledge into causal diagrams and drawing causal diagrams under different assumptions

Teaches how to use causal diagrams to identify common biases and guide data analysis, enhancing research validity

Presents real-world case studies to demonstrate the practical applications of causal diagrams in health and social sciences

Reviews summary

Positive reviews of causal diagrams course

Learners say this well-prepared course is highly recommended, even for students without experience. The course is clear, engaging, and manageable with great graphics and lots of repetition.

Students of all levels indicate the course is manageable.

"It was very well done... I was able to continue."

"And for those like me, who have no reason to take it other than curiosity, it's manageable."

Learners appreciate the clear explanations.

"It was very well done, with clear explanations"

"this class is really good to review and begin to learn about causal DAG or structural causal inference"

Learners describe the course as motivating and engaging.

"Excellent course, well prepared and very motivating."

"I finished the course with a surprisingly good grade, since I have absolutely no background in data science."

Activities

Be better prepared before your course. Deepen your understanding during and after it. Supplement your coursework and achieve mastery of the topics covered in Causal Diagrams: Draw Your Assumptions Before Your Conclusions with these activities:

Read Pearl's Causality

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Gain a comprehensive understanding of causal inference by exploring Pearl's seminal work. This book provides a theoretical foundation and practical insights into the concepts covered in the course.

View Causality: Models, Reasoning and Inference on Amazon

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Read through the book, taking notes and highlighting key concepts
Work through the exercises and examples provided in the book
Engage in discussions or write summaries to reinforce your understanding

Review prerequisite mathematics

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Revisit your foundational knowledge by reviewing significant concepts and techniques in mathematics relevant to the course, such as probability, inference, and regression.

Browse courses on Mathematics

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Review mathematical principles such as random variables, probability distributions, and hypothesis testing
Consider working through practice problems and examples to reinforce your understanding
Connect the mathematical concepts to real-world applications and scenarios

Explore Python libraries for data analysis

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Enhance your understanding of the course material by exploring Python libraries commonly used in data analysis. This will provide a practical foundation for working with real-world datasets.

Browse courses on Python

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Identify and research popular Python libraries such as Pandas, NumPy, and Scikit-learn
Follow tutorials and documentation to learn the basics of data manipulation, visualization, and statistical modeling
Experiment with these libraries on small datasets to gain hands-on experience

Four other activities

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Participate in online discussions

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Engage with your peers in online discussions to exchange ideas, ask questions, and clarify concepts. This will foster a sense of community and enhance your understanding.

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Join the course discussion forums
Pose questions and actively participate in discussions
Read and respond to your peers' posts

Develop a causal diagram for a real-world problem

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Apply the concepts of causal diagrams to a practical problem. This will help you develop a deeper understanding of the causal relationships and potential biases involved.

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Identify a real-world problem that you are interested in
Construct a causal diagram that represents the relationships between the variables involved
Analyze the causal diagram to identify potential biases and confounding factors
Present your causal diagram and findings to others for feedback

Create a presentation on causal diagrams

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Solidify your understanding by creating a presentation that explains the concepts of causal diagrams. This will help you organize your knowledge and effectively communicate it.

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Gather information and resources on causal diagrams
Structure your presentation with a clear introduction, body, and conclusion
Use visuals and examples to illustrate the concepts
Practice delivering your presentation to get comfortable and confident

Attend a causal inference workshop

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Immerse yourself in a workshop setting to enhance your understanding and practical skills in causal inference. This provides an opportunity to learn from experts and engage in hands-on activities.

Browse courses on Causal Inference

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Identify and research upcoming causal inference workshops
Attend the workshop and actively participate in the sessions
Engage with the instructors and other participants

Career center

Learners who complete Causal Diagrams: Draw Your Assumptions Before Your Conclusions will develop knowledge and skills that may be useful to these careers:

Public Health Researcher

Public health researchers investigate the causes of disease and other health problems in populations. Causal diagrams are a key tool for public health researchers, as they allow them to understand the relationships between different variables and identify the factors that are most likely to improve public health. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective public health researcher.

See salaries and explore the career path for Public Health Researcher

Statistician

Statisticians collect, analyze, and interpret data. Causal diagrams are a key tool for statisticians, as they allow them tovisualize and understand the relationships between different variables. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective statistician.

See salaries and explore the career path for Statistician

Quantitative Analyst

Quantitative Analysts analyze data to find meaningful trends and patterns that can help businesses make better decisions. Causal diagrams are a key tool for quantitative analysts, as they allow them to visualize and understand the relationships between different variables. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective quantitative analyst.

See salaries and explore the career path for Quantitative Analyst

Epidemiologist

Epidemiologists investigate the causes of disease and other health problems. Causal diagrams are a key tool for epidemiologists, as they allow them to identify the factors that are most likely to cause a particular health problem. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective epidemiologist.

See salaries and explore the career path for Epidemiologist

Policy Analyst

Policy analysts develop and evaluate policies to address public problems. Causal diagrams are a key tool for policy analysts, as they allow them to understand the relationships between different variables and identify the factors that are most likely to achieve desired policy outcomes. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective policy analyst.

See salaries and explore the career path for Policy Analyst

Health Economist

Health economists apply economic principles to the study of health and healthcare. Causal diagrams are a key tool for health economists, as they allow them to understand the relationships between different variables and identify the factors that are most likely to improve health outcomes. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective health economist.

See salaries and explore the career path for Health Economist

Program Evaluator

Program evaluators assess the effectiveness of programs and interventions. Causal diagrams are a key tool for program evaluators, as they allow them to identify the factors that are most likely to contribute to a program's success or failure. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective program evaluator.

See salaries and explore the career path for Program Evaluator

Data Scientist

Data scientists use data to solve business problems. Causal diagrams are a key tool for data scientists, as they allow them to understand the relationships between different variables and identify the factors that are most likely to cause a desired outcome. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective data scientist.

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Consultant

Consultants provide advice to businesses and organizations on how to improve their performance. Causal diagrams are a key tool for consultants, as they allow them to understand the relationships between different variables and identify the factors that are most likely to improve organizational outcomes. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective consultant.

See salaries and explore the career path for Consultant

Social Scientist

Social scientists study human behavior and society. Causal diagrams are a key tool for social scientists, as they allow them to understand the relationships between different variables and identify the factors that are most likely to influence human behavior. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective social scientist.

See salaries and explore the career path for Social Scientist

Business Analyst

Business analysts help businesses improve their performance. Causal diagrams are a key tool for business analysts, as they allow them to understand the relationships between different variables and identify the factors that are most likely to improve business outcomes. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective business analyst.

See salaries and explore the career path for Business Analyst

Market Researcher

Market researchers study consumer behavior and trends. Causal diagrams are a key tool for market researchers, as they allow them to understand the relationships between different variables and identify the factors that are most likely to influence consumer behavior. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective market researcher.

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Risk Analyst

Risk analysts identify and assess risks to businesses and organizations. Causal diagrams are a key tool for risk analysts, as they allow them to understand the relationships between different variables and identify the factors that are most likely to cause a risk to occur. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective risk analyst.

See salaries and explore the career path for Risk Analyst

Financial Analyst

Financial analysts evaluate the financial performance of companies and make recommendations on investment opportunities. Causal diagrams are a key tool for financial analysts, as they allow them to understand the relationships between different variables and identify the factors that are most likely to affect a company's financial performance. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective financial analyst.

See salaries and explore the career path for Financial Analyst

Economist

Economists study the production, distribution, and consumption of goods and services. Causal diagrams are a key tool for economists, as they allow them to understand the relationships between different variables and identify the factors that are most likely to affect economic outcomes. This course will help you develop the skills you need to create and interpret causal diagrams, which will make you a more effective economist.

See salaries and explore the career path for Economist