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Practical Statistics - Rules of Thumb

Apply these practical rules of thumb when running experiments to avoid common biases in the data you use to make business decisions.

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When to Use It

Use this sheet as a reference when you are running an innovation experiment and need to measure and report on the results with proper recognition of statistical factors.

Who Should Use It
Our Practical Statistics - Rules of Thumb guide is useful for anybody collecting and reporting quantitative data. Refer to this guide if you are running an experiment and asking questions like:
• What metrics should I measure?
• What size sample is appropriate?
• How can I minimize or remove bias from my sample size?
• What's the margin of error for this experiment?
• What's the confidence level of these results?
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Authors and Contributors
Tristan Kromer
Tristan Kromer works with innovation teams and leaders to create amazing products and build startup ecosystems. He has worked with companies from early stage startups with zero revenue to enterprise companies with >$1B USD revenue. (Unilever, Swisscom, Salesforce, Fujitsu, LinkedIn) Tristan has worked with over 17 technology accelerator programs and ecosystem programs such as Innovation Norway, Vinnova (Sweden), Enterprise Ireland, NEST’up (Belgium), StartSmart (Estonia) and the Innovation Partnership Program (Vietnam-Finland) With his remaining hours, Tristan volunteers his time with early stage startups and blogs at GrasshopperHerder.com.
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Practical Statistics for Quantitative Experiments

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