statsmodels.emplike.descriptive.DescStatUV.ci_var¶
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DescStatUV.
ci_var
(lower_bound=None, upper_bound=None, sig=0.05)[source]¶ Returns the confidence interval for the variance.
Parameters: lower_bound : float
The minimum value the lower confidence interval can take. The p-value from test_var(lower_bound) must be lower than 1 - significance level. Default is .99 confidence limit assuming normality
upper_bound : float
The maximum value the upper confidence interval can take. The p-value from test_var(upper_bound) must be lower than 1 - significance level. Default is .99 confidence limit assuming normality
sig : float
The significance level. Default is .05
Returns: Interval : tuple
Confidence interval for the variance
Notes
If the function returns the error f(a) and f(b) must have different signs, consider lowering lower_bound and raising upper_bound.
Examples
>>> random_numbers = np.random.standard_normal(100) >>> el_analysis = sm.emplike.DescStat(random_numbers) >>> el_analysis.ci_var() >>> 'f(a) and f(b) must have different signs' >>> el_analysis.ci_var(.5, 2)