Master Instrumental Variables
Without a Background in Math?

Master Instrumental Variables Even Without a Math Background

Designed for researchers, analysts, and graduate students, this course demystifies instrumental variable techniques, making them accessible, intuitive, and applicable to real-world empirical challenges.

Avoid the inefficiencies of piecing together fragmented resources. Gain a solid conceptual and practical understanding in hours, not weeks.

Important: This course is a high-leverage investment. It could save you thousands in tuition, textbooks, tutoring costs, and research time.

Trusted by Researchers from the World’s Top Institutions

Core Concepts Covered

Gain a solid understanding of instrumental variables and proxy methods without needing advanced math.

This course is designed for Master’s and PhD students who want to apply econometric techniques with confidence. Lessons are delivered in short, clear videos that make complex concepts easy to understand and use.

Module 1

Correlation vs Causation

Just because two things are connected (correlation) doesn’t mean one causes the other (causation)—understanding the difference can prevent costly mistakes.

Module 2

Unmeasured Confounders

Unmeasured confounders are unobserved variables that can skew your data, leading to misleading conclusions.

Module 3

Reverse
Causality

Reverse causality occurs when the effect is mistakenly thought to be the cause, leading to misguided decisions.

Module 4

Randomized Control Trials

Randomized Control Trials (RCTs) are the gold standard for testing causal effects, ensuring that outcomes are driven by the treatment, not external factors.

Module 5

Quasi-Experimental Methods

Quasi-experimental methods help researchers measure causal effects when experiments like RCTs aren’t feasible, providing valuable insights without full randomization.

Module 6

IV - Intuition

Understand how Instrumental Variables arrive to a causal effect without having to randomize.

Module 7

Natural Experiments

Natural experiments leverage real-world events to assess the impact of certain factors, offering insights when controlled experiments aren’t possible.

Module 8

Two Stage Least Squares

Understand how to model Instrumental Variables in practice.

Module 9

IV - Assumptions

Understand when Instrumental Variables work and when they do not.

Module 10

Strengths and Weaknesses of IV

Each method has its strengths and weaknesses. You can find those of IV here.

Module 11

R Computer Lab: 2SLS

Solve a research problem using Instrumental Variables with R!

Module 12

Stata Computer Lab: 2SLS

Solve a research problem using Instrumental Variables with Stata! 2SLS

Why Enroll in This Course?

Take the principles we teach inside this program to enrich and provide depth to your research papers.

Intuitive
Approach

Do not let math anxiety hold you back! Our advanced courses are accessible to even those with a limited math background.

Pedagogically Structured

We leverage the expertise of education and pedagogy professionals to design courses that are easy to understand and remember.

Immersive
Materials

Designed by a creative director and read by a professional narrator, our courses tell a visual story to engage learners and facilitate understanding.

Course Overview

Course Length

1h 50m

Modules

12 Modules

Course Author

Prof. dr. Deni Mazrekaj

Statistical Programs

Stata and R

Outcomes You Can Expect:

Upon finishing a course on Instrumental Variables, you will be able to:

Example of a certificate obtained after completing the course

Unlock Your FREE
4-Module Causal Inference Series

Gain immediate access to our intuitive causal inference series, designed for PhD and graduate students across disciplines, including those without a strong math background.
No credit card required.

“I was skeptical about how much I would be able to learn in a course without a strong math background, but this course exceeded my expectations. The instructors’ clear explanations and intuitive approach made it easy to grasp the math concepts and apply them in my work. Thank you!”

– Mark Brown

Who is this Course for?

Who Should NOT Attend this Course?

Course Packages

R and Stata Guide

  • Apply instrumental variables in R or Stata
  • Step-by-step guidance on running IV
  • Ideal for observational & experimental data
  • Identify and test valid instruments
  • Practical examples

Instrumental Variables

  • Access to 12 compact training modules
  • Halve your learning from weeks to hours
  • Receive years of research and learning compressed into just under 2 hours
  • Intuitive no math approach
  • Save time and elevate your research
  • Simplifying complex theories
RECOMMENDED

One to One Coaching

  • Instrumental Variables course
  • 1-hour personal session with a professor
  • Direct access to expert knowledge
  • Targeted feedback and actionable insights
  • Receive tailored advice
  • Gain new perspectives from an expert
  • Clarify complex concepts
satisfaction guarantee-1

At Edooko, we’re confident that if you commit to the course and apply what you learn, you’ll walk away with a top-tier understanding of the fundamentals of Instrumental Variables—even without a strong math background.

If you feel the course doesn’t deliver on that promise, simply email us at [email protected] within 5 days of purchase for a full refund. No hassle.

Most of our students say this course has completely changed how they approach Instrumental Variables—and for some, it’s been a game-changer in their academic journey.

Terms and conditions apply

Photo of prof. dr. Deni Mazrekaj

About the Course Author

This course was developed by an award winning professor, dr. Deni Mazrekaj, with the support of a dedicated team of researchers, educational specialists, and content creators.

Deni Mazrekaj is a professor of sociology at Utrecht University and an affiliated researcher at the University of Oxford. He holds a Ph.D. in Economics from KU Leuven. Deni has taught Advanced Quantitative Methods at the University of Oxford and is currently the coordinator of the Methods and Statistics course at Utrecht University. In his spare time, he is an associate editor of the interdisciplinary Nature journal Humanities & Social Sciences Communications. Deni has received several awards from the American Sociological Association, and the European Academy of Sociology for his research in sociology.

How This Course Helped Students Master IV Techniques

General Information and FAQs

Edooko courses are suitable for researchers, PhD candidates, data scientists, and anyone with a solid grasp of statistics who is seeking to enhance their understanding of quantitative methods. Our courses are not beginner-friendly.

To get the most out of our courses, we recommend that students have a solid grasp of undergraduate level statistics and mathematics. This includes a basic understanding of concepts such as probability, sampling, hypothesis testing, and regression analysis.

The assignments we give may include quizzes, problem sets, written assignments, and projects. The specific assignments will depend on the course and may vary from one module to the next.

Yes, you can enroll at any time and learn at your own pace.

At the moment we offer PayPal, Visa, Mastercard, Discover, American Express and UnionPay.

Edooko is committed to making our courses accessible to as many students as possible. To that end, we offer discounts to students with disadvantaged backgrounds and students from low-income countries. If you fall into one of these categories and are interested in taking one of our courses, please reach out to us. We are here to help you succeed.