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In this course, you will :
- This course will assist you in getting up to speed.
- teaches learners with no prior experience in experimental design how to create an A/B test for a web page, run the test, analyse the data, and make decisions based on the results of the test.
- begins by explaining exactly what A/B testing is and when it is useful.
- covers potential conversion rate strategies, as well as how to select both A and B conditions for testing
- explains how to define conversion rates, create and document case definitions, conduct a baseline analysis in Excel, and design an A/B test based on the results of the analysis
- demonstrates how to use G*Power to estimate sample size and conduct a chi-square test in Excel.
Syllabus :
1. Introduction to Experimental Testing
- Experiment is a type of study
- Features of an experiment
- Circumstances for experimental testing
- When not to do an experiment
- Systems ready for experimental testing
- Comparability of experimental conditions
2. Defining Conversions
- Trying to increase conversions
- Different types of conversions
- Case definition of conversion
- Measuring a conversion
- Considering time period for conversions
- Rates versus frequencies of conversions
3. Defining Conversion Rates
- Identify and prioritize conversions
- Operationalize counting conversions
- Document conversion case definitions
- Brainstorm denominators
- False positives and negatives
- Document denominators
- Determine time frames
4. Baseline Descriptive Analyses
- Baseline time-series analyses
- Data handling
- Baseline results as a guide
- Thinking about increasing conversions
- Strategies to increase conversions
- Planning a campaign
5. Designing the Experiment
- Designing the test
- Testing the implementation
- Choosing a test statistic
- Choosing the chi-squared test
- Chi-squared test in Excel
6. Sample Size and Statistics
- Installing G*Power
- Using G*Power
- Sample size simulation
- Planning the timeline
- Stratified analysis
- Conditional tests
7. Analyzing and Interpreting the Data
- Overall analysis approach
- Time-series analysis
- Chi-squared analysis
- Interpretation
