pystatpower.misc.observe_at_least_one_event ¶

FUNCTION	DESCRIPTION
`solve_power`	Calculate the detection power.
`solve_size`	Estimate the required sample size.
`solve_proportion`	Estimate the required event proportion.

solve_power ¶

solve_power(*, proportion: float, size: int, dist: Literal['bin', 'poisson'] = 'bin') -> float

Calculate the detection power.

PARAMETER	DESCRIPTION
`proportion`	Event proportion. TYPE: `float`
`size`	Sample size. TYPE: `int`
`dist`	The distribution of the number of events that occurred. `'bin'`: binomial distribution `'poisson'`: Poisson distribution TYPE: `Literal['bin', 'poisson']` DEFAULT: `'bin'`

RETURNS	DESCRIPTION
`float`	The power to observe at least one event.

solve_size(*, proportion: float, power: float = 0.95, dist: Literal['bin', 'poisson'] = 'bin') -> int

Estimate the required sample size.

PARAMETER	DESCRIPTION
`proportion`	Event proportion. TYPE: `float`
`power`	The detection power. 0.95 is a commonly used value for the detection power. TYPE: `float` DEFAULT: `0.95`
`dist`	The distribution of the number of events that occurred. `'bin'`: binomial distribution `'poisson'`: Poisson distribution TYPE: `Literal['bin', 'poisson']` DEFAULT: `'bin'`

RETURNS	DESCRIPTION
`int`	The required sample size.

solve_proportion(*, size: int, power: float = 0.95, dist: Literal['bin', 'poisson'] = 'bin') -> float

Estimate the required event proportion.

PARAMETER	DESCRIPTION
`size`	Sample size. TYPE: `int`
`power`	The detection power. 0.95 is a commonly used value for the detection power. TYPE: `float` DEFAULT: `0.95`
`dist`	The distribution of the number of events that occurred. `'bin'`: binomial distribution `'poisson'`: Poisson distribution TYPE: `Literal['bin', 'poisson']` DEFAULT: `'bin'`

RETURNS	DESCRIPTION
`float`	The required event proportion.