Professional Certificate in Split Testing for Accelerated Growth

• Introduction to Split Testing: Understanding the Basics, Key Concepts, and Importance
• Hypothesis Formulation for A/B Testing: Identifying Opportunities and Defining Goals
• Designing Effective Split Test Experiments: Sampling, Traffic Allocation, and Test Duration
• Data Analysis in Split Testing: Statistical Significance, Confidence Intervals, and P-values
• Interpreting Results and Deriving Actionable Insights from Split Tests
• Advanced Split Testing Techniques: Multivariate Testing, Bandit Testing, and Factorial Designs
• Common Pitfalls and Misconceptions in Split Testing: Avoiding Errors and Biases
• Tools and Platforms for Split Testing: Integrating A/B Testing into Your Workflow
• Case Studies: Real-World Examples and Success Stories of Split Testing
• Continuous Improvement: Implementing a Data-Driven Culture and Iterative Optimization