ROSS

Hi:
I have found that using Stepwise Multiple Regression with all the X’s in the Model along with Two Factor Interactions of those X’s is a useful tool to begin the screen of multiple X’s (some of which may be co-linear). Stepwise Regression is a natural way to identify & remove co-linear X’s from the model. Hope this helps. Have a great day, Tony
 

Hi Reinaldo:
I believe your question pertains to monitoring Key Process input variables that determine your Process Output. If this is the case, then I would monitor only those Key process Input Variables that significantly deterimine your Key process Output Variable. Typically, Multiple Regression Analysis or formal Design of Experiments are u…[Read more]

That is not very helpful.

no i am actually an instructor monitoring this board to see who is cheating… JUST KIDDING! -No we are not in the same class or school.

your calculation is correct.

thank you so much that helped. Very much appreciated.
Tony

here is my email: [email protected] shoot me an email and we can take it from there. No we have different instructors. most likely a different school as well. thank you so much. I am at my zero hour..

would you mind helping me out?

god I am lost…..My last answer was 5 and 40 and it was wrong. I am confused on the below where “the .0879 and 7.525 don’t include the mean value”
by the way thank you very much for your help. I so need it

i think it is of the mean. I am coming up with .0879 and 7.5250
if it is from the the mean I am coming up with 0.4896 and 41.8974

Yes a class project assignment.
The mean is 21.1935 . The standard deviation is 6.9013 . I am having trouble figuring out how to calculate the correct expected variation + or – 3 standard deviations from the mean. So far every answer I have given is wrong. The last hint from the instructor was: my mean is correct, my standard deviation is…[Read more]

It looks like we are doing the same health care project. Did you get an answer? 

During 6 sigma training, I present the concepts of Taguchi’s loss function to stress that, although inevitable, any variation is bad and has some resulting effect on customer satifaction and therefore cost of poor quality. The message is “never stop reducing variation if it is still possible within obvious commercial constraints”
I agree with…[Read more]

Calculating capacity is very easy once you know 2 things: Volume and Productivity.
Here’s a simple equation:
P(roductivity)= V(olume)/TM (Team Member)*H(ours)
The first step is know the maximum hourly productive of the Team Members (TM), (e.g.) if TM 1 has an hrly productivity of 8, TM 2 is 6, and TM 3 is 4 – then (assuming that each TM is…[Read more]

I am also interested in receiving a copy of the storyboard for the mortage processing cycle … would greatly appreciate if you could send to me by email also.
Thanks
 

I agree with Daves point. There is a non-linear relationaship between dBm and mW and the distribution of the data in each type of unit should be explored to ensure normality by transformation if necessary. At the end of the day “which unit of measure is most important to the customer – dBm of mV”? That is the one that should be used.

I have the customer specs already in my database. I just need a matmatical equation that I can use to determine the sigma value using the specs as well as the deviation value. Any idea?

I agree that at the “company” level there are no Six Sigma performers.  However, if you look at processes, there are many.
One of the classic examples is aircraft safety as defined by number of passenger flights without casualties vs total flights taken.  This process is much higher than Six Sigma, and we wouldn’t tolerate much less.  Baggage ha…[Read more]

Here is an older example:
Suppliers: Cain, Abel
Customer: God
Specification: Animal offering (blood sacrifice)
Customer received from Cain: Fruit of the ground
Customer received from Abel: Animal offering
Result: Abel’s offering accepted, Cain’s offering rejected
COPQ: Jealousy–> murder–> Cain cursed by God
Lesson:  Know your…[Read more]

Proven data-driven continuous improvement methodology.