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The confidence coefficient is also known as the confidence level or degree of confidence. It is the percent expression for the probability, 1-α, that the confidence interval contains the true population parameter assuming that the confidence interval is obtained after sufficient unbiased sampling; for example, if the CL = 90%, then in 90 out of 100 samples the interval estimate will enclose the true population parameter. Here α is the area under the curve, distributed equally under both the tails of the curve. Further, this area indicates the levels of statistical significance. Mathematically, α + CL = 1.

The confidence coefficient is essential for the interpretation of the confidence interval. Three commonly used confidence coefficients are 0.90, 0.95, and 0.99. For these three confidence coefficients, the value of α is 0.1, 0.05, and 0.01, respectively. These coefficients can also be expressed as a percentage – 90%, 95%, and 99%, respectively.

For example, using a confidence level of 95%, where α is 0.05, a researcher can confidently say that 95% of all of the calculated confidence intervals will contain the true population parameter value.

This text is adapted from Openstax, Introductory Statistics, Section 8, Confidence Interval

Tags
Confidence CoefficientConfidence LevelDegree Of ConfidenceStatistical SignificanceConfidence IntervalPopulation ParameterUnbiased SamplingArea Under The CurveConfidence CoefficientsPercent ExpressionMathematical ExpressionOpenstaxIntroductory Statistics

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7.4 : Confidence Coefficient

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7.1 : 什么是估计值?

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7.2 : 样本比例和总体比例

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7.3 : 置信区间

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7.5 : 置信区间的解释

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7.6 : 临界值

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7.7 : 误差幅度

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7.8 : 样本量计算

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7.9 : 使用已知标准差估计总体均值

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7.10 : 估计具有未知标准差的总体均值

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7.11 : 用于估计总体均值的置信区间

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