Experimentation

Explain Like I am 5 | 7-Day Summary

Explain Like I’m Five Series | Understanding Null and Alternate Hypotheses and MDE. Understanding P-value. What is the level of significance?

Mar 13 • Manisha Arora

Explain Like I am 5 | Day 06: Understanding P-Values

Explain Like I’m Five Series | Lesson 06 - Understanding P-value. One core experimentation concept, explained with clarity and practical intuition.

Mar 11 • Manisha Arora

Explain Like I am 5 | Day 04: Understanding Null and Alternate Hypotheses

Explain Like I’m Five Series | Lesson 04 -Understanding Null and Alternate Hypotheses. One core experimentation concept, explained with clarity and…

Mar 9 • Manisha Arora

Beyond Wins and Losses: How to Learn from Inconclusive A/B Tests

A practical framework for extracting learning when experiments don’t reach statistical significance.

Feb 12 • Manisha Arora and Banani Mohapatra

Experimentation Is a Game of Tradeoffs: Here’s How to Navigate Them

How leading teams make confident decisions under experimental uncertainty.

Jan 30 • Manisha Arora and Banani Mohapatra

Cracking A/B Testing Interviews

A behind-the-scenes look at how top product data teams evaluate A/B testing interviews. Learn how to think in terms of intent, metrics, and decisions …

Jan 25 • Manisha Arora, Siddarth, and Banani Mohapatra

A Simple Framework to Structure Any A/B Testing Interview Question - Part 1/2

Master a simple four-step framework (Objective → Metrics → Design → Decision) to turn any experiment question into a clear, strategic answer…

Jan 13 • Manisha Arora and Banani Mohapatra

Beyond Statistical Significance: Designing Robust A/B Tests

Join Manisha Arora and Banani Mohapatra at #GHC25 to explore how top teams design smarter experiments that drive real business impact — beyond just…

Oct 22, 2025 • Manisha Arora and Banani Mohapatra

Choosing the Right Causal Inference Method

A practical guide for data scientists on mapping real-world business problems to the right causal inference framework — from experiments to…

Sep 30, 2025 • Manisha Arora

A Practical Guide to Difference-in-Differences — A 5-Part Series Summary

A quick recap of our 5-part series on Difference-in-Differences — from intuition to implementation and robustness checks. A practical guide for applying…

Jul 31, 2025 • Manisha Arora and Banani Mohapatra

Part 4: Running Robustness Checks in Diff-in-Diff

In this post, we walk through key robustness checks—from outlier analysis to placebo tests and diagnostics—to ensure your causal claims stand on solid…

Jul 25, 2025 • Manisha Arora and Banani Mohapatra

Part 3B: Measuring the Impact of Free Shipping: a Diff-in-Diff Case Study

Using Difference-in-Differences, we estimate the true causal impact of offering free shipping—beyond assumptions and surface-level metrics.

Jul 23, 2025 • Manisha Arora and Banani Mohapatra

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