Independent trial
An independent trial is a random experiment whose outcome probabilities are unaffected by the outcomes of other trials.
Statistics Every Programmer Needs
An independent trial is a random trial whose outcome does not alter the probabilities of outcomes in other trials.
- How it is used
- Models repeated binary outcomes for binomial probability calculations in manufacturing, healthcare, and market research.
- How deep it goes
- Defines constant probabilities and demonstrates binomial PMF calculations for fixed trial counts.
- Examples
- Uses 20-trial distributions with success probabilities of 0.20, 0.50, 0.75, and 0.90, plus an exactly-seven-success calculation.
- What you can do after
- Apply it via SciPy's binom.pmf or the binomial formula to calculate exact-success probabilities.
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Statistics Slam Dunk
An independent trial is an random experiment whose outcome probability is unaffected by the outcomes of other trials.
- How it is used
- Uses independent trials to model coin flips and evaluate whether free-throw streaks reflect randomness rather than a hot-hand effect.
- How deep it goes
- Defines independence and demonstrates its implementation through repeated sampling with replacement.
- Examples
- Uses fair-coin simulations, streaks of heads or tails, and NBA free-throw sequences as examples.
- What you can do after
- Apply it via R's sample() function to simulate equally likely, independent coin flips with replacement.
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