pystatpower.mean.single.ci ¶

FUNCTION	DESCRIPTION
`solve_precision`	Calculate the distance from the mean to the confidence limit (commonly known as precision).
`solve_size`	Estimate the required sample size.
`solve_std`	Estimate the required standard deviation.

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 mean to the confidence limit (commonly known as precision).

PARAMETER	DESCRIPTION
`std`	Standard deviation. TYPE: `float`
`size`	Sample size. TYPE: `int`
`conf_level`	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 TYPE: `float` DEFAULT: `0.95`
`interval_type`	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. TYPE: `Literal['two-sided', 'one-sided', 'lower', 'upper']` DEFAULT: `'two-sided'`
`dist`	The distribution used to construct the confidence interval. `'z'`: Normal distribution. `'t'`: Student's t-distribution. TYPE: `Literal['z', 't']` DEFAULT: `'t'`

RETURNS	DESCRIPTION
`float`	The distance from the mean to the confidence limit (commonly known as precision).

Notes

Since the confidence interval for the 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.

PARAMETER	DESCRIPTION
`precision`	Distance from the mean to the confidence limit. TYPE: `float`
`std`	Standard deviation. TYPE: `float`
`conf_level`	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 TYPE: `float` DEFAULT: `0.95`
`interval_type`	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. TYPE: `Literal['two-sided', 'one-sided', 'lower', 'upper']` DEFAULT: `'two-sided'`
`dist`	The distribution used to construct the confidence interval. `'z'`: Normal distribution. `'t'`: Student's t-distribution. TYPE: `Literal['z', 't']` DEFAULT: `'t'`

RETURNS	DESCRIPTION
`int`	The required sample size.

Notes

Since the confidence interval for the 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.

PARAMETER	DESCRIPTION
`precision`	Distance from the mean to the confidence limit. TYPE: `float`
`size`	Sample size. TYPE: `int`
`conf_level`	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 TYPE: `float` DEFAULT: `0.95`
`interval_type`	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. TYPE: `Literal['two-sided', 'one-sided', 'lower', 'upper']` DEFAULT: `'two-sided'`
`dist`	The distribution used to construct the confidence interval. `'z'`: Normal distribution. `'t'`: Student's t-distribution. TYPE: `Literal['z', 't']` DEFAULT: `'t'`

RETURNS	DESCRIPTION
`float`	The required standard deviation.

Notes

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