Learn how to optimize and understand your statistics. If you’re not fluent in A/B testing statistics, you won’t be able to tell whether your tests suck. How to conduct A/B testing with sound statistical design. How to ask the right questions and avoid common errors, while gaining insights from statistics.

ConversionXL (Georgi Georgiev) – Statistics for AB Testing

Be a true optimizer Know your statistics

If you’re not fluent in A/B testing statistics, you won’t be able to tell whether your tests suck.

Many of your “winning” There are no winners in tests. Be able to recognize when you are being bullied and advocate for a scientific approach within your team.

In 8 sessions, you’ll learn

• How to run A/B testing with sound statistical design
• How to ask the right questions and avoid common mistakes.
• A in-Deep understanding of statistical hypothesis testing concepts and concepts such as statistical significance, confidence intervals and statistical power.

Understanding the complexities of planning and evaluating A/B testing

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.

This is the right path for you if…

• You can’t define statistical significance correctly without looking it up on Google.
• The A/B tests can produce many results “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 are a member of the in-You can use the house statistic tool that you are trying to improve or a third-party one.-Party A/B Testing Software you Want to Understand Better

This is probably not the right course. for you if…

• You are new to CRO and you have very little or no experience in 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.

These are the skills you need to have in order to take this course.

• Some expertise in conversion rate optimization.
• An overview of the principles behind A/B Testing.
• Experience with A/B testing software.

Your instructor
Georgi Georgiev

He’s the mastermind behind Analytics-Toolkit.com is a SaaS service that is used by web analysts from all over the world and CROs from agencies worldwide.

Georgi Georgiev owns WebFocus, which is a digital consulting firm that provides world-class digital marketing services.-Analytics and marketing services in class for The past 10 years.

Georgi is a lecturer in multiple marketing events, as well as a Google Regional Trainer in AdWords & Analytics. He is also the author or multiple articles about A/B testing. for Optimize conversion rates

In just 8 sessions, you’ll be able to

• It is important to plan the most efficient A/B testing.
• Correctly interpret A/B testing stats.
• Navigate the MVT, segmentation and multiple KPIs that are involved in concurrent tests.
• You can plan and analyze sequential tests.

The complete course curriculum

Statistics for A/B testing

Lesson 1

What is the A/B test? Basics of causal deduction

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 Develop a probabilistic mindset

The following topics are covered:

• Correlation is causal. Controlled experiments versus observational analysis.
• Sampling and natural variation and their implications for Drawing insights from data
• Null-Hypothesis statistical tests – History and basics of causal inference
• Control and randomization in A/B testing – Why are they important and how do they work?
• One-One-sided and two-Side-by-side tests, composite vs. the point hypothesis.

Lesson 2

Statistical significance & confidence intervals

Conversion rate optimization is a very popular area where statistical significance is often misused. This is how it works. We’ll discuss common misuses and misunderstandings, their consequences, and how to avoid them.

The following topics are covered:

• What is statistical significance?
• Here are some common mistakes in statistical significance.
• How to avoid common misinterpretations
• A/A, B/A, and A/A/B/B Testing – When are they appropriate, how can they be used, and why? for?
• Confidence intervals

Lesson 3

Planning A/B tests: Sample size & statistical power

Why is statistical power so vital, yet so overlooked? Learn about trade-What are the steps involved in A/B testing planning? How can you avoid getting too many or too few?-Powered tests

The following topics are covered:

• What is statistical power, and why is it important?
• The relationship between power and other statistical parameters: significance, sample size, & minimum detectable effect.
• Below-Powerful and over-Powered tests

Lesson 4

Multivariate testing & concurrent tests

How to correctly plan and analyze multivariate testing, while avoiding common pitfalls. This article will discuss the appropriate use of concurrent tests and when it is appropriate.

The following topics are covered:

• Complexities can be created by testing multiple variants versus the control.
• What is the difference between an A/B/n and a simple A/B test.
• Do’s and don’ts of running concurrent tests

Lesson 5

Segmentation, multiple KPIs, & non-binomial tests

Segmentation is a way to get deeper insights. We’ll also examine the fine details of using multiple outcome metrics for Cover non-insured and tested-Binomial metrics like revenue per user are examples.

The following topics are covered:

• Segmenting A/B testing data for maximum insights.
• Complexities of running tests that have more than one outcome
• Analyzing non-Binomial data, such as revenue or time on site, can be used.

Lesson 6

Sequential testing

Sequential testing will be the future of A/B Testing. Discover the different methods of sequential testing and how to plan and analyse a sequential test.

The following topics are covered:

• Classical fixed is not perfect-Tests samples
• Optional stopping
• The alpha-Sequential testing is best approached with a spending approach
• Analyzing and planning a sequential test
• Benefits and drawbacks of adaptive tests

Lesson 7

You can test faster by asking the right questions

How do we make A/B tests run efficiently? Designing and analysing them to answer the questions we are looking for.

The following topics are covered:

• One vs. Two-Tests of significance for tailed
• Non-Infektion testing
• Non-traditional hypothesis and analysis

Lesson 8

Planning ROI-Positive A/B tests

The cherry on top? How to combine all seven courses into highly efficient A/B testing that yields great returns.

The following topics are covered:

• Benefits and costs in A/B Testing
• Planning ROI-Positive A/B tests

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