Confidence Interval
In statistics, an interval that expresses the uncertainty of an estimate, usually paired with a confidence level such as 95%. The width of the interval reflects the precision of the estimate.
Timeline (last 90 days)
Conditional intervals and confidence intervals are constructed differently: conditional intervals ignore the multiple-comparison problem introduced by model selection and thus tend to be narrower, while confidence intervals attempt to cover the true parameter value; the widths of the two are not directly comparable, and whether intervals overlap does not directly correspond to ranking significance.
If the confidence interval crosses zero, the null hypothesis of no effect cannot be rejected; the interval width reflects precision, and the smaller the sample and the larger the variance, the wider the interval.
A confidence interval represents the range into which the true value may fall at a given confidence level (such as 95%); the wider the interval, the greater the prediction uncertainty, and business decisions should be more cautious.
If the data exhibit long memory, using the traditional √γ confidence interval will severely underestimate uncertainty, and inference must be based on a scale of γ^{β-1/2}ℓ(1/γ).
校准的不确定性区间意味着：若模型声称 90% 置信区间为某范围，则在大量测试样本中约 90% 的真实值应落入该范围。
For slice evaluations containing only a few hundred samples, a reasonable confidence interval is often as wide as 3–5 percentage points.
Evaluation results are better expressed using confidence intervals rather than point estimates, and reporting a pass-rate interval is more honest than reporting a single number.
The 95% confidence interval for β1 can be constructed via β1 ± 2·SE(β1), meaning that in approximately 95% of repeated sampling and modeling instances the true β1 falls within that interval.
All Facts (8)
Conditional intervals and confidence intervals are constructed differently: conditional intervals ignore the multiple-comparison problem introduced by model selection and thus tend to be narrower, while confidence intervals attempt to cover the true parameter value; the widths of the two are not directly comparable, and whether intervals overlap does not directly correspond to ranking significance.
50%UnverifiedIf the confidence interval crosses zero, the null hypothesis of no effect cannot be rejected; the interval width reflects precision, and the smaller the sample and the larger the variance, the wider the interval.
50%UnverifiedA confidence interval represents the range into which the true value may fall at a given confidence level (such as 95%); the wider the interval, the greater the prediction uncertainty, and business decisions should be more cautious.
50%UnverifiedIf the data exhibit long memory, using the traditional √γ confidence interval will severely underestimate uncertainty, and inference must be based on a scale of γ^{β-1/2}ℓ(1/γ).
50%Unverified校准的不确定性区间意味着：若模型声称 90% 置信区间为某范围，则在大量测试样本中约 90% 的真实值应落入该范围。
50%UnverifiedFor slice evaluations containing only a few hundred samples, a reasonable confidence interval is often as wide as 3–5 percentage points.
50%UnverifiedEvaluation results are better expressed using confidence intervals rather than point estimates, and reporting a pass-rate interval is more honest than reporting a single number.
50%UnverifiedThe 95% confidence interval for β1 can be constructed via β1 ± 2·SE(β1), meaning that in approximately 95% of repeated sampling and modeling instances the true β1 falls within that interval.
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