Avoid Preformance Testing Data Deception
Don't be fooled by your performance test results. Performance testing can easily generate an unwieldy amount of data-some relevant and some not. Testers and their tools often use statistical methods to make sense of the data, but using statistics requires sacrificing accuracy and thoroughness. The good news is that we do not need to understand all the details to make good use of test results. The challenge is to determine what information really matters and how to present it in a useful manner. Join Ben Simo as he addresses common performance test statistical problems including built-in bias, agreeable averages, invisible inadequacies, gargantuan groupings, stingy sets, mountainous molehills, creative charting, alien alliances, and more. Find out how statistical reporting can deceive rather than inform-often unintentionally-and recognize what the numbers do not say. By learning how to tell the truth with performance test results, you can give your stakeholders the information they really need to make good decisions.
- What is takes to understand performance data
- How to protect yourself from misinformation
- Provide useful and understandable performance information to stakeholders
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