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FMEA ( Failure Mode & Effect Analysis )
In Six Sigma DMAIC methodology, most traditional Six Sigma consultants / training instructors advocate the use of FMEA ( typically Process FMEA ) in Measure / Analyze phase. The project leaders were normally taught on how to use FMEA to … Continue reading
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Correlation & Regression Part 2
In previous blog, it was shown how to make use of scatterplot to detect linear trend and correlation analysis to quantify Pearson correlation coefficient value. The Pearson correlation coefficient value was determined as 0.999 ( positive correlated ) and it … Continue reading
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Correlation & Regression Part 1
Correlation analysis is to quantify the degree to which the variables are related, i.e. how well the estimating equation fits. Regression analysis is about construction of an estimating equation that relates the predictor/s to the response. In fact, correlation analysis … Continue reading
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How to proceed Analyze phase? Hypothesis Testing – Part 11 ( Chi Square Test )
Chi Square Test is used to test proportions of > 2 sample data. Following is a case study to illustrate it’s application. The process engineer would like to know if different raw material ( type A, B & C ) … Continue reading
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How to proceed Analyze phase? Hypothesis Testing – Part 10 (2proportion Test)
Following is a case study related to the application of 2proportion test. Currently, there were 5 production lines running the same product. All the 5 production lines were using the same version of machines. A process engineer would like to … Continue reading
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How to proceed Analyze phase ? Hypothesis Testing – Part 9 ( 1proportion test )
In the previous blogs Hypothesis Testing ( Part 1 – 8 ), the statistical tools covered were related to “mean(m)” and “Variance(σ/σ2)”. In this blog onward, “Proportion(p)” will be discussed. Basically, proportion data is derived from the ratio of binary … Continue reading
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