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Murat Unal
Murat Unal

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Published in Towards Data Science

·Mar 7

Why are Randomized Experiments the Gold Standard in Causal Inference?

Understanding the identifying assumptions in experiments — Causal inference without assumptions is impossible. Every available method requires untestable assumptions to establish causality from observed associations in the data. As such, stating the identifying assumptions and defending them is the most critical aspect of causal inference, yet it is also the most neglected one. In my previous article…

Causal Inference

7 min read

Why are Randomized Experiments the Gold Standard in Causal Inference?
Why are Randomized Experiments the Gold Standard in Causal Inference?
Causal Inference

7 min read


Mar 1

What is the Value of Improving the Customer Experience in E-Commerce?

Improve customer experience and increase engagement at your online store by simplifying checkout. — The Customer Experience Among the three stages in the customer’s journey with a business, namely, pre-purchase, purchase, and post-purchase, the purchase stage is key in shaping customer experience because it is related to several key behaviors, such as choice, ordering, and payment [1]. As such, a long and complicated checkout process, in particular…

Causal Inference

7 min read

What is the Value of Improving the Customer Experience in E-Commerce?
What is the Value of Improving the Customer Experience in E-Commerce?
Causal Inference

7 min read


Published in Towards Data Science

·Feb 22

Identification: The Key to Credible Causal Inference

Improve your causal IQ and build trust in your causal inference by mastering identification — Causal inference is the process by which we use data to make claims about causal relationships, thus it is among the core tasks of data scientists. …

Causal Inference

8 min read

Identification: The Key to Credible Causal Inference
Identification: The Key to Credible Causal Inference
Causal Inference

8 min read


Published in Towards Data Science

·Feb 7

Variance Reduction in Experiments — Part 2: Covariate Adjustment Methods

Deep dive into MLRATE - machine learning regression-adjusted treatment effect estimator and comparing it to other methods — This is the second post in the series of articles where we are discussing variance reduction in experiments. …

Causal Inference

9 min read

Variance Reduction in Experiments — Part 2: Covariate Adjustment Methods
Variance Reduction in Experiments — Part 2: Covariate Adjustment Methods
Causal Inference

9 min read


Published in Towards Data Science

·Feb 2

Variance Reduction in Experiments — Part 1: Intuition

The intuition behind variance reduction and why it is important in randomized experiments. — This is the first part in a series of two articles where we are going to dive deep into variance reduction in experiments. In this article we are going to discuss why variance reduction is necessary and build an intuition behind its mechanism. …

Causal Inference

7 min read

Variance Reduction in Experiments  — Part 1: Intuition
Variance Reduction in Experiments  — Part 1: Intuition
Causal Inference

7 min read


Published in Towards Data Science

·Jan 18

An Intuitive Explanation for Inverse Propensity Weighting in Causal Inference

Understanding the roots of inverse propensity weighting through a simple example. — One of the well-established methods for causal inference is based on the Inverse Propensity Weighting (IPW). In this post we will use a simple example to build an intuition for IPW. …

Causal Inference

8 min read

An Intuitive Explanation for Inverse Propensity Weighting in Causal Inference
An Intuitive Explanation for Inverse Propensity Weighting in Causal Inference
Causal Inference

8 min read

Murat Unal

Murat Unal

128 Followers

Economist @ Amazon | Cornell University Ph.D.

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