pystatpower.proportion.single.ci ¶

FUNCTION	DESCRIPTION
`solve_distance`	Calculate the confidence interval width or the distance from the proportion to the confidence limit.
`solve_size`	Estimate the required sample size.
`solve_proportion`	Estimate the required proportion.

solve_distance ¶

solve_distance(
    *,
    proportion: float,
    size: int,
    conf_level: float = 0.95,
    interval_type: Literal["two-sided", "lower", "upper"] = "two-sided",
    method: Literal["wald", "wilson", "clopper-pearson", "cp"] = "cp",
    continuity_correction: bool = False,
) -> float

Calculate the confidence interval width or the distance from the proportion to the confidence limit.

PARAMETER	DESCRIPTION
`proportion`	Proportion. TYPE: `float`
`size`	Sample size. TYPE: `int`
`conf_level`	Confidence level. If `interval_type` is `'two-sided'`, a two-sided confidence level is required. If `interval_type` is `'lower'` or `'upper'`, a one-sided confidence level is required. TYPE: `float` DEFAULT: `0.95`
`interval_type`	Type of the confidence interval. `'two-sided'`: Two-sided confidence interval. `'lower'`: Lower one-sided confidence interval. `'upper'`: Upper one-sided confidence interval. TYPE: `Literal['two-sided', 'lower', 'upper']` DEFAULT: `'two-sided'`
`method`	The method used to construct the confidence interval. `'wald'`: Wald method. `'wilson'`: Wilson method. `'clopper-pearson'`, `'cp'`: Clopper-Pearson method. TYPE: `Literal['wald', 'wilson', 'clopper-pearson', 'cp']` DEFAULT: `'cp'`
`continuity_correction`	Whether to apply the continuity correction, only takes effect when `method` is specified as `'wald'` or `'wilson'` TYPE: `bool` DEFAULT: `False`

RETURNS	DESCRIPTION
`float`	The confidence interval width or the distance from the proportion to the confidence limit. If `alternative` is `'two-sided'`, the confidence interval width is returned. If `alternative` is `'less'`, the distance from the proportion to the confidence limit is returned.

solve_size ¶

solve_size(
    *,
    proportion: float,
    distance: float,
    conf_level: float = 0.95,
    interval_type: Literal["two-sided", "lower", "upper"] = "two-sided",
    method: Literal["wald", "wilson", "clopper-pearson", "cp"] = "cp",
    continuity_correction: bool = False,
) -> int

Estimate the required sample size.

For two-sided confidence interval, the confidence interval width is required.

For one-sided confidence interval, the distance from the proportion to the confidence limit is required.

PARAMETER	DESCRIPTION
`proportion`	Proportion. TYPE: `float`
`distance`	If `interval_type` is `'two-sided'`, a confidence interval width is required. If `interval_type` is `'lower'` or `'upper'`, a distance from the proportion to the confidence limit is required. TYPE: `float`
`conf_level`	Confidence level. If `interval_type` is `'two-sided'`, a two-sided confidence level is required. If `interval_type` is `'lower'` or `'upper'`, a one-sided confidence level is required. TYPE: `float` DEFAULT: `0.95`
`interval_type`	Type of the confidence interval. `'two-sided'`: Two-sided confidence interval. `'lower'`: Lower one-sided confidence interval. `'upper'`: Upper one-sided confidence interval. TYPE: `Literal['two-sided', 'lower', 'upper']` DEFAULT: `'two-sided'`
`method`	The method used to construct the confidence interval. `'wald'`: Wald method. `'wilson'`: Wilson method. `'clopper-pearson'`, `'cp'`: Clopper-Pearson method. TYPE: `Literal['wald', 'wilson', 'clopper-pearson', 'cp']` DEFAULT: `'cp'`
`continuity_correction`	Whether to apply the continuity correction, only takes effect when `method` is specified as `'wald'` or `'wilson'` TYPE: `bool` DEFAULT: `False`

RETURNS	DESCRIPTION
`int`	The required sample size.

solve_proportion ¶

solve_proportion(
    *,
    size: int,
    distance: float,
    conf_level: float = 0.95,
    interval_type: Literal["two-sided", "lower", "upper"] = "two-sided",
    method: Literal["wald", "wilson", "clopper-pearson", "cp"] = "cp",
    continuity_correction: bool = False,
    direction: Literal["greater", "less"] = "greater",
) -> float

Estimate the required proportion.

For two-sided confidence interval, the confidence interval width is required.

For one-sided confidence interval, the distance from the proportion to the confidence limit is required.

PARAMETER	DESCRIPTION
`size`	Sample size. TYPE: `int`
`distance`	If `interval_type` is `'two-sided'`, a confidence interval width is required. If `interval_type` is `'lower'` or `'upper'`, a distance from the proportion to the confidence limit is required. TYPE: `float`
`conf_level`	Confidence level. If `interval_type` is `'two-sided'`, a two-sided confidence level should is required. If `interval_type` is `'lower'` or `'upper'`, a one-sided confidence level is required. TYPE: `float` DEFAULT: `0.95`
`interval_type`	Type of the confidence interval. `'two-sided'`: Two-sided confidence interval. `'lower'`: Lower one-sided confidence interval. `'upper'`: Upper one-sided confidence interval. TYPE: `Literal['two-sided', 'lower', 'upper']` DEFAULT: `'two-sided'`
`method`	The method used to construct the confidence interval. `'wald'`: Wald method. `'wilson'`: Wilson method. `'clopper-pearson'`, `'cp'`: Clopper-Pearson method. TYPE: `Literal['wald', 'wilson', 'clopper-pearson', 'cp']` DEFAULT: `'cp'`
`continuity_correction`	Whether to apply the continuity correction, only takes effect when `method` is specified as `'wald'` or `'wilson'` TYPE: `bool` DEFAULT: `False`
`direction`	The search direction for the proportion relative to the 0.5. `'greater'`: Search for the proportion greater than 0.5. `'less'`: Search for the proportion less than 0.5. TYPE: `Literal['greater', 'less']` DEFAULT: `'greater'`

RETURNS	DESCRIPTION
`float`	The required proportion.