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  Statistical Techniques and 6 Sigma
  Gage R&R Confidence Intervals

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Author Topic:   Gage R&R Confidence Intervals
Ben
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posted 21 November 2000 03:40 PM           Edit/Delete Message   Reply w/Quote
Reference AIAG's MSA Reference Manual, page 95, "Confidence Intervals"

Does anyone know of a supplemental text I can go to in order to figure out how to determine confidence intervals for a gage R&R study?

I apologize, but I cannot interpret the phrase "where MS denotes percentage point for a mean square distribution (i.e., a Chi-square deviate with the same degree of freedom divided by degrees of freedom, v)"

Thank you.

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Marc Smith
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posted 07 January 2001 06:23 PM     Click Here to See the Profile for Marc Smith   Click Here to Email Marc Smith     Edit/Delete Message   Reply w/Quote
Any statistical gurus out there with a comment or 2 on this?

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max
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posted 08 January 2001 10:55 AM           Edit/Delete Message   Reply w/Quote
The formulas might be in some SPC texts. Here is a journal reference:

"Gauge Capability Analysis and Designed Experiments. Part II: Experimental Design Models and Variance Component Estimation" by Montgomery and Runger, Quality Engineering, Vol. 6, No. 2, OCTOBER 1993, pp. 289-305.

(part I: Quality Engineering, Vol. 6, No. 1, JULY 1993, pp. 115-135)

As for "where MS denotes percentage point for a mean square distribution (i.e., a Chi-square deviate with the same degree of freedom divided by degrees of freedom, v)": if you use ANOVA to get your results from the study, there will be mean squares for part, operator and so on. Each mean square has a specific degree of freedom associated with it. These numbers (the df) are needed to compute the confidence interval.

For example, we performed an R&R study with 16 parts. There are 16-1=15 degrees of freedom for the part source of variation in the study. If I wanted to get the 5th percentage point for a Chi-square distribution with 15 df, Excel would give it to me with CHIINV(0.05,15), which is 24.99.

Consult the references above. They are written for non-statisticians.

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