Design and analyze A/B tests and experiments — frame the hypothesis and metric, compute the required sample size and power, run the significance test (proportions z-test, means t-test), report confidence intervals and lift, and avoid the classic traps (peeking, multiple comparisons, underpowered tests, p-hacking). Includes a stdlib calculator for sample size, significance, and CIs. Use when the user is planning or analyzing an experiment, asks about statistical significance, sample size, conversion-rate tests, or whether a result is real.
How to install ab-testing?
nocetic/flowly/ab-testing
$npx -y skills add nocetic/flowly --skill ab-testingInstalls into the current project.
›Prefer a prompt? Paste this to your agent
Run `npx skills use "https://github.com/nocetic/flowly" --skill "nocetic/flowly/ab-testing"` and follow the generated skill instructions now. Read its complete output, redirecting it to a temporary file first if necessary. Resolve relative paths from the supporting-files directory it provides.
Use the skills in "https://github.com/nocetic/flowly" that are relevant to the current task. Run `npx skills add "https://github.com/nocetic/flowly"` and select the relevant skills, then follow their instructions.
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