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Remi replied to the topic Non normal data in the forum Methodology 11 years, 4 months ago
Hai gsx,
Why did you do this? ie why do you want to make the data ‘Normal’ ?
It doesn’t help you solve the problem.
Counted data will not be normal distributed in general.And no: I would not trust any data manipulated in this way.
Remi

Remi replied to the topic Calculating Process Capability for Wait Time at a Restaurant in the forum Methodology 11 years, 5 months ago
Hai Awylan,
whenever I have a data set that contains a lot of 0’s I split my capability analysis of the CTQ in two.
CTQ1= % nonzero’s; Target is very often 0; goal of project part1 to reduce average value and variation of CTQ1
CTQ2 = CTQ if CTQ is nonzero. target = 0; goal of project2 to improve Cpk and reduce values.
By splitting this up…[Read more] 
Remi replied to the topic Gage R and R on historical data – how to? in the forum General 11 years, 8 months ago
hi BMWSAND,
your formula assumes that the data only has variation caused by the measuring process.
Remi 
Remi replied to the topic Gage R and R on historical data – how to? in the forum General 11 years, 8 months ago
Hai The Kid,
You can’t. A gage r&R study is an experiment you do to investigates the quality of your datacollection/measurement. Unless you can perform that experiment you cannot do a gage r&R.
This doesn’t mean that your old data is worthless. only that you can’t proof that it can be trusted.
So the only way forward is: Write down in your r…[Read more] 
Remi replied to the topic PPM equivalent for multiple characteristics in the forum General 11 years, 9 months ago
Hi Mark,
as a first approximation you could sum them up.
More correct is to compensate for products that have more than one characteristic failing. If the characteristics occur independently of each other you get the following calculation (if not a similar formula can be derived but you have to count the multiple occurences).
Pi = P (char i…[Read more] 
Remi replied to the topic Outlier in the forum Finance 11 years, 9 months ago
Hi outlier,
No, Boxplot does not use normality; it is distribution free. What happens is: IF Data is Normal distr. THEN (1.5*IQR and 3* Stdev give the same value) and (Median and Mean give the same value). So in that case points further than 1.5*IQR happen to cross the +/ 3S line.For detecting potential outliers mathematicians have calcu…[Read more] 
Remi replied to the topic Sales force Vs Production Schedules in the forum General 11 years, 9 months ago
Hai Mike,
You already wrote in your message a solution: the problem (as seen by you) is created by Sales that has to get to target in Q4.A simple (uncacceptable by Mgt?) solution is to arrange for Sales Quarter targets. Then your Year problem changes into a Quarter problem. If that is still too rough change it into a Month problem etc.
Better i…[Read more] 
Remi replied to the topic Guage R R, Anova in the forum Software/IT 11 years, 9 months ago
Anshu,
for a Six Sigma project you generally only use the tools that you need (for making the project a success). Since nobody knows beforehand which those will be a lot of them are covered in the GB course .
BUT
if you are doing a six sigma project to get certified, the certifier wants you to show him/her that you are Capable of doing Six…[Read more] 
Remi replied to the topic Bimodal Cpk correction in the forum General 11 years, 9 months ago
Hai MBBinWI,
thanks for the advice. I didn’t see that Oops until you mentioned it. You are right.
Remi 
Remi replied to the topic Outlier in the forum Finance 11 years, 9 months ago
Hai Outlier,
distributions don’t have outliers, whether normal or not.
If you mean “how can I see if a datapoint is an outlier in a data set that does not follow a normal distribution”:
– make a graph (dotplot, histogram,…)
– if you see a point ‘far away’ (purely subjective eyeball mark1 measurement) investigate WHY that point is different…[Read more] 
Remi replied to the topic Rolled throughput yield for parallel processes in the forum Europe 11 years, 9 months ago
Hai Choochor,
make a process mapping (=flow chart) of the process steps.There is 1 input location (=entry).Put 1.000.000 product(part)s in the process entry. Write down for every process step how many parts (of the 1.000.000) enter that process step (calculate from parallelsplitup) and how many leave the process step (calculated from RTY of…[Read more] 
Remi replied to the topic DOE with Discreet data in the forum General 11 years, 9 months ago
Hai KD,
the correct answer is: it depends.
If y = air usage, it does not matter how the holes are placed. The air usage is the Area of all the holes together.
If Y = cooling strength on a small area, then situation with holes all near the centre gives a different result than holes on the border.
So the question is: what is your Y=CTQ and how…[Read more] 
Remi replied to the topic taguchi loss function in the forum General 11 years, 9 months ago
Hai Darth_X,
here is a way to do it.
Input is LSL, T(arget), USL.
1] you have to choose a formula for the lossfunction. THE LOSSFUNCTION does not exist (as far as I know); an often mentioned one is the quadratic form L=K*(yT)*(yT) where the K is the lossfactor. If you have T = (USL+LSL)/2 (i.e. in the middle) you can determine K if you…[Read more] 
Remi replied to the topic DOEattribute in the forum General 11 years, 10 months ago
Hai Anthony,
Ask your experts to give a score on the quality of the mark on a scale of 1 to 10: a “5” is considered perfect marking; a “1” is for ‘burned’ and a “10” is for ‘no mark’. In this way you have a ranking of the laser marking from ‘too much’ (1) through ‘good’ (5) until ‘too little’ (10).Use this score as the Y of your DoE analysis a…[Read more] 
Remi replied to the topic Gage RR for 3 and 10 operators in the forum General 11 years, 10 months ago
Hai Boon,
I don’t know your template but general the answer is NO.
First a warning: be carefull with the sentence “to measure the Gage R&R of the QC technicians”. Operator is only part of the variation sources. A gage r&R investigates the consequences of all variation source of measurement variation (that happen during the experiment). So if…[Read more] 
Remi replied to the topic Normality in the forum General 11 years, 10 months ago
hai Darth,
in my answer I mentioned that the residuals should be normal distributed. Y= f(x) + error; the ANOVA analysis can be usedIFF ((error is normal distributed) AND (equal variances test is passed)).
I realize that “error is Normal” is not exactly the same as “each of the groups is normal” but don’t remember enough of my statistics to say…[Read more] 
Remi replied to the topic Normality in the forum General 11 years, 10 months ago
Susan,
So you have 2884 lengths of fishes divided over 8 groups.
First make a picture: boxplot and decide if you want to perform analyssi on all the data or if some of the points should be analysed different.
Then do 1Way ANOVA.
The data itself does not have to be normal distributed (and often is not if there is a large meandifference); but…[Read more] 
Remi replied to the topic ANOVA Variance Component – Urgent in the forum General 11 years, 11 months ago
Sorry Sathya, but your explanation of boxplotconclusions is WRONG.
Duplicate the datasets sever times (make sample Size artificially high). The boxplots will not be different; the Mean and StDev do ‘not’ change; but the pvalues will get arbitrary low: the larger you make the N the smaller the Pvalue gets.
Remi

Remi replied to the topic Sample size calculation for Binary Data in the forum General 11 years, 11 months ago
Euh Max,
I expect that all your managers will have moved to a new job before you have enough data with only 4 data/year.
Forget this approach and put all your effort into finding a way to get data more often (and of the contiuous type). The good news is that you have at least 3 months before the next datapoint makes your question a little bit…[Read more] 
Remi replied to the topic exclude factors after DOE in the forum General 11 years, 11 months ago
Hai K,
yes and No. You could do it but the 3d factor may influence the result as a lurking factor.
Example.
Suppose your ‘real (unknown) model’ is: Y= X1 + X2 + 20*X3 + 100*X1*X3If you leave out the significant X3 two things happen (both bad for conclusions):Your SSE (error=noise) gets large due to 20*X3 so your Rsq will drop to a low…[Read more]
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