pystatpower.models.proportion.single.ci ¶

Functions:

Name	Description
`solve_size`	Estimate the sample size required to achieve a given confidence interval for one proportion.
`solve_ci_width`	Calculate the confidence interval width for one proportion.
`solve_proportion`	Estimate the proportion required to achieve a given confidence interval for one proportion.

solve_size ¶

solve_size(proportion: float, ci_width: float, alpha: float = 0.05, method: str = 'clopper_pearson', continuity_correction: bool = False) -> float

Estimate the sample size required to achieve a given confidence interval for one proportion.

Parameters:

Name	Type	Description	Default
`proportion`	`float`	Proportion.	required
`ci_width`	`float`	Confidence interval width.	required
`alpha`	`float`	Significance level. Default is 0.05.	`0.05`
`method`	`str`	Specify the method for calculating confidence interval. Default is `clopper_pearson`.	`'clopper_pearson'`
`continuity_correction`	`bool`	Specify whether or not the continuity correction is used, only valid for `method` = `wald` or `wilson`. Default is False.	`False`

Returns:

Name	Type	Description
`size`	`float`	The required sample size.

solve_ci_width ¶

solve_ci_width(proportion: float, size: float, alpha: float = 0.05, method: str = 'clopper-pearson', continuity_correction: bool = True) -> float

Calculate the confidence interval width for one proportion.

Parameters:

Name	Type	Description	Default
`proportion`	`float`	Proportion.	required
`size`	`float`	Sample size.	required
`alpha`	`float`	Significance level. Default is 0.05.	`0.05`
`method`	`str`	Specify the method for calculating confidence interval. Default is `clopper_pearson`.	`'clopper-pearson'`
`continuity_correction`	`bool`	Specify whether or not the continuity correction is used, only valid for `method` = `wald` or `wilson`. Default is False.	`True`

Returns:

Name	Type	Description
`ci_width`	`float`	The confidence interval width.

solve_proportion ¶

solve_proportion(size: float, ci_width: float, alpha: float = 0.05, method: str = 'clopper_pearson', continuity_correction: bool = False, side: str = 'upper') -> float

Estimate the proportion required to achieve a given confidence interval for one proportion.

Parameters:

Name	Type	Description	Default
`size`	`float`	Sample size.	required
`ci_width`	`float`	Confidence interval width.	required
`alpha`	`float`	Significance level. Default is 0.05.	`0.05`
`method`	`str`	The method for calculating confidence interval. Default is `clopper_pearson`.	`'clopper_pearson'`
`continuity_correction`	`bool`	Whether or not the continuity correction is used, only valid for `method` = `wald` or `wilson`. Default is False.	`False`
`side`	`str`	Which root to return. Must be `lower` (proportion closer to 0) or `upper` (proportion closer to 1). Default is `upper`.	`'upper'`

Returns:

Name	Type	Description
`ci_width`	`float`	The confidence interval width.