The mainstream confidence interval limits are normally set at LL=sqrt(Sd1^2/(Sd2^2*F(n1-1,n2-1,alpha1))) and UL= sqrt((Sd1^2/(Sd2^2))*F(n2-1,n1-1,alpha2))), where:

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The confidence interval for the CP index is calculated by evaluating the following expressions: LLCp = Cp * Sqrt(CHI_Square_Value(1 – alpha/2, N - 1) / (N - 1)) and ULCp = Cp * sqrt(CHI_Square_Value(alpha, N - 1) / (N - 1)).

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In medical research differences in proportions are an important effect measure for randomized controlled trial (RCT) and cohort studies. In manufacturing the production manager may need to compare the proportion of defectives produced by two different processes.

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The following information is directed at proportions but also applicable to ppm as ppm is directly related to proportions. Proportions are based on underlying discreet (and hence are not on a continuous) scale as for the mean sampled from a Normal distribution.

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Proportions are based on underlying discreet (and hence are not on a continuous) scale as for the mean sampled from a Normal distribution. Consider a sample size of 10 sampled from a Normal Population.

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In medical research differences in proportions are an important effect measure for randomized controlled trial (RCT) and cohort studies.

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The confidence interval for the CP index is calculated by evaluating the following expressions: LLCp = Cp * Sqrt(CHI_Square_Value(1 – alpha/2, N - 1) / (N - 1)) and ULCp = Cp * sqrt(CHI_Square_Value(alpha, N - 1) / (N - 1)).

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