experiment-design
Design statistically rigorous experiments to test data science hypotheses. Use when the user says "design an A/B test", "run an experiment", "test this hypothesis", "is this difference significant", "how many samples do I need", "randomized controlled trial", "causal inference", "uplift test", "holdout group", "significance test", "power calculation", "avoid p-hacking", or needs to determine whether an observed effect is real before making a product or model decision.
Installation and usage
Design statistically rigorous experiments to test data science hypotheses. Use when the user says "design an A/B test", "run an experiment", "test this hypothesis", "is this difference significant", "how many samples do I need", "randomized controlled trial", "causal inference", "uplift test", "holdout group", "significance test", "power calculation", "avoid p-hacking", or needs to determine whether an observed effect is real before making a product or model decision.
์ค์น ํ ํฐ๋ฏธ๋์์ ๋ค์ ๋ช ๋ น์ ์คํํ์ฌ ์ด ์คํฌ์ ์ฌ์ฉํ ์ ์์ต๋๋ค:
skills use experiment-design