Statistics for A/B testing
Become a proper optimizer and know your stats. If you’re not fluent in A/B testing statistics, you won’t be able to tell whether your tests suck. A lot of your “winning” tests are probably not winners at all. Learn to call bullshit when needed, and be the person who advocates proper scientific approach in your team.
In this 8class training program, you'll learn:

How to run A/B tests with a sound statistical design.

How to ask the right questions, avoid common mistakes, and get insights through statistics.

An indepth understanding of statistical hypothesis testing and concepts like statistical significance, confidence intervals, statistical power, and others.
This course is right for you if...
 You can’t define statistical significance correctly without looking it up on Google.
 Your A/B tests produce a lot of “winners,” but your clients aren’t seeing improvements.
 You’re planning and analyzing A/B tests, but you don’t understand the statistical underpinnings of the testing process.
 You're not confident in the outcomes of your tests and are unsure how much trust to put in them
 You have an inhouse statistical tool you want to improve, or you use a thirdparty A/B testing software you want to understand better
This course is NOT for you if...
 You are just starting with CRO and have little to no practical experience with A/B testing.
 You don’t employ A/B tests as a primary method to evaluate CRO work.
 You are a professional statistician or experimental design specialist.
Skills you should have...

Some experience in conversion rate optimization.

Basic understanding of how A/B testing works.

Some experience with an A/B testing software.
This class will give you all the tools you need to understand the complexities involved in planning and evaluating A/B tests.
Aside from mining specific information, you’ll get deeper and more accurate insights from your data in the process.
Avoid costly testing mistakes stemming from misuse and misunderstanding of statistics, and improve the ROI of all your A/B testing efforts, with Georgi Georgiev’s guidance.
About your instructor:
Georgi Georgiev
Georgi Georgiev is the owner of WebFocus, a digital marketing consulting company delivering worldclass marketing and analytics services for the past 10 years.
He’s the mastermind behind AnalyticsToolkit.com, a SaaS used by web analysts and CRO practitioners from agencies across the world.
Georgi is a lecturer in multiple marketing events, as well as a Google Regional Trainer in AdWords & Analytics. He is also the author of three papers and multiple articles on A/B testing for conversion rate optimization.
Why we handselected Georgi to teach this course
Georgi is thinking about and solving the problems most folks in CRO don't have the training or the time to pursue. After you've learned from him, you'll be able to apply experimental analyses that can save you lots of sample size and test runtime for your experimentation program.
Talking with Georgi for only a few minutes reveals an incredible depth of knowledge that rivals and often surpasses trained statisticians working in more theoretical disciplines. The value he brings is one of practical application, strikingly simple explanations of complex mathematical concepts, and a deep passion for the craft of CRO.
In just 8 sessions, you’ll be able to:
 Plan maximally efficient A/B tests.
 Correctly interpret A/B testing statistics.
 Navigate the complexities of MVT, segmentation, multiple KPIs, and concurrent tests.
 Plan and analyze sequential tests.
Course curriculum:
Statistics for A/B testing
Class 1
Why A/B test? Basics of causal inference
In the first class, we’ll lay the groundwork that's required in order to understand more advanced concepts in subsequent classes. We’ll go over basic concepts that are crucial for developing a probabilistic mindset.
Topics covered:
 Correlation and causation. Observational analysis versus controlled experiments.
 Sampling and natural variance and their implications for drawing insights from data.
 Nullhypothesis statistical tests – history and basics of causal inference.
 Control and randomization in A/B tests – why we need them and how they work?
 Onesided and twosided tests, composite vs. point hypothesis.
Class 2
Statistical significance & confidence intervals
Statistical significance is one of the most abused concepts in conversion rate optimization. You will learn what it is, really. We’ll discuss common misuses and misunderstandings, their consequences, and how to avoid them.
Topics covered:
 What is statistical significance.
 Common misuses of statistical significance and how to avoid them.
 Common misinterpretations and how to avoid them.
 A/A, A/B/A, A/A/B/B testing – when are they appropriate, and what can they be used for?
 Confidence intervals.
Class 3
Planning A/B tests: Sample size & statistical power
Why is statistical power so important, and yet so neglected? You will learn about the tradeoffs involved in planning A/B tests, and how to avoid under and overpowered tests.
Topics covered:
 What is statistical power and why does it matter?
 The relationship between power and other statistical parameters: significance, sample size, & minimum detectable effect.
 Underpowered and overpowered tests.
Class 4
Multivariate testing & concurrent tests
Learn how to properly plan and analyze a multivariate test, avoiding common pitfalls. We examine the practice of running multiple concurrent tests, and how and when it's appropriate.
Topics covered:
 Complexities introduced by testing more than one variant versus control
 When is an A/B/n test preferred to a simple A/B test?
 Do’s and don’ts of running concurrent tests
Class 5
Segmentation, multiple KPIs, & nonbinomial tests
Learn how to gain deeper insights by segmentation. We’ll also examine the fine details of using multiple outcome metrics for a test and cover nonbinomial metrics such as revenue per user.
Topics covered:
 Segmenting A/B testing data for maximum insights.
 Complexities in running tests with more than one outcome metric.
 Analyzing nonbinomial data such as revenue and time on site.
Class 6
Sequential testing
Sequential testing is the future of A/B testing. Learn about different approaches to sequential testing, and how to plan and analyze a sequential test.
Topics covered:
 Shortcomings of classical fixedsample tests
 The issue of optional stopping
 The alphaspending approach to sequential testing
 Planning and analyzing a sequential test
 Adaptive tests – benefits and drawbacks
Class 7
Faster testing by asking the right questions
How can we run A/B tests with maximum efficiency? By designing and analyzing them to reflect the questions we want answered.
Topics covered:
 One vs twotailed significance tests
 Noninferiority testing
 Nontraditional hypothesis and analysis
Class 8
Planning ROIpositive A/B tests
The cherry on top: how to combine everything from the past seven courses to run highly efficient A/B tests that result in great returns.
Topics covered:
 Costs and benefits in A/B testing
 Planning ROIpositive A/B tests
You will also get introductory
video lessons
In addition to classes, you’ll get access to snacksized video lessons to bring you up to speed on the course topics. Topics include:
1. Why is A/B testing hard?
2. Intuitive probability vs. probability in testing
3. A/B testing as risk management
4. Knowing your A/B testing tools
Show Off Your New Skills: Get a Certificate of Completion
Once the course is over, pass a test to get certified in Statistics for A/B Testing
Add it to your resume, your LinkedIn profile or just get that wellearned raise you’ve been waiting for.
Need help convincing your boss to pay for this? Share this with your manager
ENROLL NOW — $499.00
Teams of 2 and more get a 25% discount during checkout.
After completing the payment you can login to the course homepage. 7day money back guarantee.