chapters · 6
01Free Preview
Metrics That Matter: Vanity Vs Actionable
Learn to distinguish between metrics that look good and metrics that actually drive decisions
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A/b Testing: Statistical Significance
Understand when test results are real patterns versus random noise
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Correlation Vs Causation: Common Mistakes
Learn why ice cream sales and drowning deaths correlate, but ice cream doesn't cause drowning
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Sample Bias: Why Polls Get It Wrong
Understand how sampling errors led to wrong election predictions and business decisions
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Statistical Significance: When To Trust Results
Learn the basics of p-values and confidence intervals to make better data-driven decisions
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Data Visualization: Seeing Patterns
Discover how the right chart reveals insights instantly while the wrong one obscures truth
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