Introducing ELIF A/B Testing Edition
Launching Explain Like I'm Five, A/B Testing Series. One concept at a time, explained clearly, practically, and without the jargon!
A few weeks ago, I put up a simple post asking if people would be interested in a series where I break down A/B testing concepts in the simplest way possible.
I didn’t expect the response I got.
The interest, the comments, the DMs — it was clear that many of us feel the same thing.
Experimentation is powerful.
But it can also feel… overwhelming.
We hear terms like causal inference, bias-variance tradeoff, p-values, and confidence intervals. We’ve read the definitions.
But do they truly click?
So after working on this quietly for the past few weeks, I’m officially launching:
Explain Like I’m Five (ELI5) — A/B Testing Edition
👋 Hey! This is Manisha Arora from PrepVector. Welcome to the Tech Growth Series, a newsletter that aims to bridge the gap between academic knowledge and practical aspects of data science. My goal is to simplify complicated data concepts, share my perspectives on the latest trends, and share my learnings from building and leading data teams.
Every single day, we’ll pick one important A/B Testing concept and break it down into the simplest possible explanation.
No academic overload.
No unnecessary jargon.
No intimidating math (unless absolutely needed).
Just:
Clear intuition
Simple analogies
Practical examples
Why it actually matters in real-world product and business decisions
How it works
Posts:
3 concepts per week. Short. Sharp. Practical.
Weekly Wrap-Up:
At the end of each week, we’ll compile all the concepts into a structured, easy-to-reference newsletter edition — refined, organized, and expanded with additional insights.
Think of it as building your mental models — one brick at a time.
Over time, you won’t just “know” the terms.
You’ll understand how they connect.
If you’re a data, product, or tech professional who wants stronger fundamentals — this series is for you.
👉 Subscribe to the newsletter to receive the weekly deep-dive summary directly in your inbox.
Let’s make complex ideas simple.
One day. One concept. One clear explanation at a time.
If you’d like to dive deeper into experimentation, here are a few of our learning programs you might enjoy:
A/B Testing Course for Data Scientists and Product Managers
Learn how top product data scientists frame hypotheses, pick the right metrics, and turn A/B test results into product decisions. This course combines product thinking, experimentation design, and storytelling—skills that set apart analysts who influence roadmaps.
Advanced A/B Testing for Data Scientists
Master the experimentation frameworks used by leading tech teams. Learn to design powerful tests, analyze results with statistical rigor, and translate insights into product growth. A hands-on program for data scientists ready to influence strategy through experimentation.
Master Product Sense and AB Testing, and learn to use statistical methods to drive product growth. I focus on inculcating a problem-solving mindset, and application of data-driven strategies, including A/B Testing, ML, and Causal Inference, to drive product growth.
Not sure which course aligns with your goals? Send me a message on LinkedIn with your background and aspirations, and I’ll help you find the best fit for your journey.
This is a great idea, I probably have many of the statistical concepts but A/B testing is discussed on LinkedIn as a kind of sorcery