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7.4 : Confidence Coefficient

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

From Chapter 7:

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7.4 : Confidence Coefficient

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7.1 : What are Estimates?

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7.2 : Sample Proportion and Population Proportion

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7.3 : Confidence Intervals

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7.5 : Interpretation of Confidence Intervals

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7.6 : Critical Values

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7.7 : Margin of Error

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7.8 : Sample Size Calculation

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7.9 : Estimating Population Mean with Known Standard Deviation

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7.10 : Estimating Population Mean with Unknown Standard Deviation

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7.11 : Confidence Interval for Estimating Population Mean

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