What do you mean by Statistical Significance?
Statistical significance refers to the level of confidence that the differences you observe in the test are not due to chance.
- For instance, it can help you determine if the higher click-through rates for Variant B are statistically significant. Statistical significance is usually expressed as a p-value, which is the probability of getting the observed results by chance.
- A lower p-value indicates a higher level of statistical significance.
- A common threshold for statistical significance is 0.05, which means there’s only a 5% chance that the results are due to chance.
- Tools like Evan Miller’s calculator or Optimizely’s calculator can be used to calculate the statistical significance of your A/B test results.
A/B Testing Framework
A/B testing is a proven way to improve your online strategy by comparing two versions of a webpage or app and seeing which one performs better based on user behavior. This article focuses on discussing the A/B testing framework.
Table of Content
- What is A/B Testing?
- Why Should You Consider A/B Testing?
- What Can You A/B Test?
- Types of A/B Testing
- Statistical Approach to use to Run A/B Test
- Steps to Conduct an A/B Test
- A/B Testing Process
- What are Variant A and Variant B?
- What is the Conversion Rate?
- What do you mean by Statistical Significance?
- Mistakes to Avoid While A/B Testing
- Challenges in A/B Testing
- A/B Testing and SEO
- Conclusion
- FAQs
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