pystatpower.mean.single.ci ¶

Functions:

Name	Description
`solve_precision`	Calculate the distance from the single-group mean to the confidence limit (commonly known as precision).
`solve_size`	Estimate the required sample size, given the distance from the single-group mean to the confidence limit (commonly known as precision).
`solve_std`	Estimate the required standard deviation, given the distance from the single-group mean to the confidence limit (commonly known as precision).

solve_precision ¶

solve_precision(
    *,
    std: float,
    size: int,
    conf_level: float = 0.95,
    interval_type: Literal[
        "two-sided", "one-sided", "lower", "upper"
    ] = "two-sided",
    dist: Literal["z", "t"] = "t",
) -> float

Calculate the distance from the single-group mean to the confidence limit (commonly known as precision).

Parameters:

Name	Type	Description	Default
`std`	`float`	Standard deviation.	required
`size`	`int`	Sample size.	required
`conf_level`	`float`	Confidence level. If `interval_type` is `'two-sided'`, a two-sided confidence level should be specified If `interval_type` is `'one-sided'`, `'lower'` or `'upper'`, a one-sided confidence level should be specified	`0.95`
`interval_type`	`Literal['two-sided', 'one-sided', 'lower', 'upper']`	The type of confidence interval. `'two-sided'`: Two-sided confidence interval. `'one-sided'`: One-sided confidence interval. `'lower'`: Lower one-sided confidence interval. `'upper'`: Upper one-sided confidence interval.	`'two-sided'`
`dist`	`Literal['z', 't']`	The distribution used to construct the confidence interval. `'z'`: Normal distribution. `'t'`: Student's t-distribution.	`'t'`

Returns:

Name	Type	Description
`float`	`float`	The distance from the single-group mean to the confidence limit (commonly known as precision).

Notes

Since the confidence interval for the single-group mean is symmetric, specifying interval_type as 'lower', 'upper', or 'one-sided' works consistently.

solve_size ¶

solve_size(
    *,
    precision: float,
    std: float,
    conf_level: float = 0.95,
    interval_type: Literal[
        "two-sided", "one-sided", "lower", "upper"
    ] = "two-sided",
    dist: Literal["z", "t"] = "t",
) -> int

Estimate the required sample size, given the distance from the single-group mean to the confidence limit (commonly known as precision).

Parameters:

Name	Type	Description	Default
`precision`	`float`	Distance from the single-group mean to the confidence limit.	required
`std`	`float`	Standard deviation.	required
`conf_level`	`float`	Confidence level. If `interval_type` is `'two-sided'`, a two-sided confidence level should be specified If `interval_type` is `'one-sided'`, `'lower'` or `'upper'`, a one-sided confidence level should be specified	`0.95`
`interval_type`	`Literal['two-sided', 'one-sided', 'lower', 'upper']`	The type of confidence interval. `'two-sided'`: Two-sided confidence interval. `'one-sided'`: One-sided confidence interval. `'lower'`: Lower one-sided confidence interval. `'upper'`: Upper one-sided confidence interval.	`'two-sided'`
`dist`	`Literal['z', 't']`	The distribution used to construct the confidence interval. `'z'`: Normal distribution. `'t'`: Student's t-distribution.	`'t'`

Returns:

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

Notes

Since the confidence interval for the single-group mean is symmetric, specifying interval_type as 'lower', 'upper', or 'one-sided' works consistently.

solve_std ¶

solve_std(
    *,
    precision: float,
    size: int,
    conf_level: float = 0.95,
    interval_type: Literal[
        "two-sided", "one-sided", "lower", "upper"
    ] = "two-sided",
    dist: Literal["z", "t"] = "t",
) -> float

Estimate the required standard deviation, given the distance from the single-group mean to the confidence limit (commonly known as precision).

Parameters:

Name	Type	Description	Default
`precision`	`float`	Distance from the single-group mean to the confidence limit.	required
`size`	`int`	Sample size.	required
`conf_level`	`float`	Confidence level. If `interval_type` is `'two-sided'`, a two-sided confidence level should be specified If `interval_type` is `'one-sided'`, `'lower'` or `'upper'`, a one-sided confidence level should be specified	`0.95`
`interval_type`	`Literal['two-sided', 'one-sided', 'lower', 'upper']`	The type of confidence interval. `'two-sided'`: Two-sided confidence interval. `'one-sided'`: One-sided confidence interval. `'lower'`: Lower one-sided confidence interval. `'upper'`: Upper one-sided confidence interval.	`'two-sided'`
`dist`	`Literal['z', 't']`	The distribution used to construct the confidence interval. `'z'`: Normal distribution. `'t'`: Student's t-distribution.	`'t'`

Returns:

Name	Type	Description
`float`	`float`	The required standard deviation.

Notes

Since the confidence interval for the single-group mean is symmetric, specifying interval_type as 'lower', 'upper', or 'one-sided' works consistently.