Statistics and A/B Testing for Analysts

Data Analytics

Statistics and A/B Testing for Analysts

Know when a result is real. Learn the statistics analysts use every day, from confidence intervals to A/B tests, explained through simulation before formulas.

Intermediate
10 weeks
Online · Synchronous
Cost TBD

Key details

Track at a Glance

Program: Data Analytics
Track level: Intermediate
Cohort length: 10 weeks
Cohort number: 1
Cohort size per section: 25
Number of sections: 1
Cohort schedule: TBD
Live sessions: One 120-minute session per week
Live sessions schedule: TBD
Self-study: About 4–8 hours per week (recommended)
Total time: About 60–100 hours
Format: Online – Synchronous
Orientation: TBD
Credential: Certificate of completion from iVERT
Prerequisite: Track 4 or basic Python and pandas
Program cost: TBD
Registration period: TBD

All students must attend orientation. Otherwise, they will be dropped.

Overview

Charts can show a pattern that is only noise. This Track gives you the tools to tell the difference, and to explain uncertainty to people who need a clear yes or no.

Ideas are taught by simulation first, so you see why they work before you use the formulas. You finish by designing and analyzing an A/B test and writing a decision memo.

This Track is for you if you

Analyze data and want to back your findings with evidence
Want to work in product, growth, marketing, or research analytics
Found statistics confusing before and want a practical, visual approach

It is not designed for

Theoretical or university-level mathematical statistics
Learners without basic Python (take Track 4 first)

By the end of the Track

What You Will Learn

Explain variation, sampling, and why patterns can be noise
Calculate and interpret confidence intervals, including by simulation
Run and interpret common hypothesis tests, and report effect size
Fit and explain a simple regression, and spot confounding
Recognize pitfalls: p-hacking, multiple comparisons, and Simpson’s paradox
Design an A/B test: hypothesis, metrics, sample size, and randomization
Write a clear decision memo from experiment results

10 weeks

Track Outline

Learn the fundamentals, build with realistic data, and excel by presenting your work.

Week 1
Learn
Thinking statistically

Samples, variation, and why a difference in the data is not always a real difference.
Weeks 2–3
Learn
Sampling and confidence intervals

Distributions, the sampling distribution, and confidence intervals, built first by simulation.
Weeks 4–5
Build
Hypothesis tests and effect size

p-values and what they are not; t-tests, proportion tests, and chi-square. Mini-project 1 due in week 5.
Weeks 6–7
Build
Regression and relationships

Correlation and linear regression; interpreting coefficients; confounding and Simpson’s paradox.
Week 8
Build
Designing A/B tests

Hypotheses, primary and guardrail metrics, sample size, and common pitfalls. Mini-project 2 (an experiment plan) due in week 8.
Weeks 9–10
Excel
Capstone

Analyze an A/B test and present a ship, don’t-ship, or run-longer decision.

TBD Successful candidates Closing and certification

How you are graded

Assessment and Certificate

Component	Weight	What it covers
Weekly practice sets	20%	Scenario-based exercises, with worked solutions
Short quizzes	15%	Interpretation over formulas
Mini-projects (2)	25%	Written comments and one resubmission on each
Capstone	40%	A/B test analysis and decision memo

Certificate of completion: awarded to learners who score 70% or higher with an acceptable capstone. You get written comments on projects, an answer key for practice sets, and one resubmission on each mini-project.

What you will build

Analyze a real A/B test dataset: check the setup, estimate the effect with a confidence interval, and write a one-page decision memo with your recommendation and its limits. You keep the notebook and memo as portfolio pieces.

Tools and Materials

All student materials are free.

Notebooks

Google Colab with SciPy and statsmodels (free)

Simulations

Short interactive notebooks to build intuition

Practice data

Public experiment datasets and realistic business scenarios

Learning platform

iVERT’s E-Learning site for materials, quizzes, submissions, and recordings

Community channel

Discord or Slack for quick questions and peer help

Prerequisites and Enrollment Requirements

Required

Track 4, or the ability to load and summarize data with pandas
A computer with a modern browser and reliable internet access
Willingness to think carefully about evidence and uncertainty

Helpful, not required

High-school algebra
Experience making decisions from reports

Not required

Calculus, a statistics degree, or paid software.

After this Track

Career Fit and What Comes Next

Skills you will leave with

Confidence intervals
Hypothesis testing
Effect size
Regression
Experiment design
A/B test analysis
Decision memos

Where these skills apply

Product or growth analyst
Marketing analyst
Research analyst
M&E specialist
Data analyst (full scope)

Experimentation skills set candidates apart for product and growth roles.

MORE TRACKS

Explore the Data Analytics Tracks

See every Track in this Program and choose your next step.

Finish here with a certificate and a portfolio project, or continue. Either is a good outcome.

Browse all Tracks

How to Apply

Check that you meet the prerequisites above.
Take note of the Program, Track, and Cohort number (needed to apply).
Use the button below to apply, or to register your interest if the Track has a waitlist.
Watch your email for confirmation and onboarding details.

Applications are not open for this Track right now. See which Tracks are open, or request information and we will let you know when the next Cohort opens.

Track FAQs: Find Quick Answers

I struggled with math at school. Can I do this?

Yes. We build ideas with pictures and simulations first, and focus on interpretation rather than derivations.

Why is Python required?

Simulations and tests run in short Python notebooks. You need to load and summarize data with pandas, which Track 4 covers.

Is A/B testing only for tech companies?

No. The same ideas apply to programs, campaigns, pricing, and service changes anywhere.

What if I miss a session?

Sessions are recorded and posted on the learning platform, and you can ask questions at office hours.

How much time will I need each week?

About 6–10 hours: one 120-minute live session plus 4–8 hours of self-study.

Will this get me a job?

iVERT does not place graduates or guarantee employment. iVERT is not an accredited college; Programs do not grant degrees or academic credit. However, you will leave with job-relevant skills and a portfolio project to show employers.

iVERT does not place graduates or guarantee employment. iVERT is not an accredited college; Programs do not grant degrees or academic credit.