Introduction
Conducting an experiment online
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What you should know
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1. Introduction to Experimental Testing
Experiment is a type of study
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Features of an experiment
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Circumstances for experimental testing
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When not to do an experiment
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Systems ready for experimental testing
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Comparability of experimental conditions
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2. Defining Conversions
Trying to increase conversions
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Different types of conversions
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Case definition of conversion
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Measuring a conversion
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Considering time period for conversions
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Rates versus frequencies of conversions
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3. Defining Conversion Rates
Identify and prioritize conversions
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Operationalize counting conversions
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Document conversion case definitions
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Brainstorm denominators
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False positives and negatives
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Document denominators
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Determine time frames
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4. Baseline Descriptive Analyses
Baseline time-series analyses
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Data handling
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Baseline results as a guide
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Thinking about increasing conversions
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Strategies to increase conversions
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Planning a campaign
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5. Designing the Experiment
Designing the test
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Testing the implementation
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Choosing a test statistic
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Choosing the chi-squared test
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Chi-squared test in Excel
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6. Sample Size and Statistics
Installing G*Power
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Using G*Power
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Sample size simulation
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Planning the timeline
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Stratified analysis
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Conditional tests
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7. Analyzing and Interpreting the Data
Overall analysis approach
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Time-series analysis
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Chi-squared analysis
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Interpretation
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Conclusion and Next Steps
What actions can we take?
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Report writing
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Ex_Files_Data_Science_Exp_Design.zip
(1.0 MB)