iSixSigma

John Noguera

Activity

  • John Noguera replied to the topic Non-normal Data in the forum General 11 years, 3 months ago

    I agree with your recommendations and the possibility of a bimodal distribution, but caution that the gaps may also be due to sampling error given the small sample size of 35.

  • John Noguera replied to the topic Non-normal Data in the forum General 11 years, 3 months ago

    Angie,
    Thanks for sharing the data. The problem you have with fitting your data is probably due to the “chunkiness” of your data, likely due to limitation in measurement discrimination.Andrew Sleeper’s book “Six Sigma Distributions” has a good discussion on this topic.
    SigmaXL found that the best fit was a three parameter loglogistic, but…[Read more]

  • Rene,
    One other thing, when you say that found some transformations that visually look to fit, I assume that the AD p-values were still <.05.  Do you see "chunky" data, i.e. vertical lines with the same values?  This takes us back to measurent discrimination. If this is the case, I would go with the transformation that gives you the best fit, r…[Read more]

  • Rene,
    Darth’s comment is correct.  In fact the reason for the non-normality and inability to transform could simply be that you have a truncated normal distribution due to the inspection.
    If this is not the case, then check for the usual suspects: outliers (with special causes), bimodal (a hidden X factor), and limited measurement d…[Read more]

  • Robert’s recommendation is good. Here are some additional things to consider:
    You might be able to use Box-Cox if you add 1 to your data and spec limits.
    Johnson is a system of non-linear transformations (logarithmic and inverse hyperbolic sine). See Minitab’s Help on Methods and Formulas.
    See also:
    Y. Chou, A.M. Polansky, and R.L. Mason…[Read more]

  • Holly,
    You have to be careful in comparing results from different analyses. One Factor ANOVA assumes that your factor is fixed, and the null hypothesis is equality of means.  On the other hand Variance Components Analysis assumes that your factor(s) is random and the null hypothesis is equality of variance.
    Having said that, using your variance…[Read more]

  • John Noguera replied to the topic CTQ in the forum General 14 years, 3 months ago

    Hey Eric,
    Love that wry sense of humor!
    John
     

  • Hi Darth,
    Thanks for your post.  Good comments regarding the scale.  Your reference paper does, in the conclusion, allow that the t-test may be somewhat robust.
    Ordinal Logistic Regression can also be used for comparisons if you dummy code the predictors.
    The challenge is what does one teach at the  Green Belt level?

  • As an analogy, the electric vacuum would be the common tool used by a general practioner.  The advanced tools would be akin to the tools used by a professional  carpet cleaner.  
    See http://www.upa.pdx.edu/IOA/newsom/da1/ho_levels.doc
    “Common PracticeAlthough Likert-type scales are technically ordinal scales, most researchers treat them as con…[Read more]

  • Likert data is ordinal. The “technically correct” analysis with this type of data is Ordinal Logistic Regression and/or Kendall’s Coefficient of Concordance and would be the tools of choice for a Statistician.
    Treating Ordinal data as continuous is however a reasonable simplifying approximation.  Therefore use of T-tests and ANOVA are not incorrect.

  • John Noguera replied to the topic Nonparametric Hyp Test in the forum General 15 years ago

    Let’s try that again:
    It depends – what is driving your non-normality – skewness, bimodal, outliers?
    If the data is symmetric or moderately skewed and n for each sample is > 15 central limit theorem will give you approximate validity.
    You can also try a box-cox transformation. If you find a suitable transformation, the same transformation must…[Read more]

  • John Noguera replied to the topic Nonparametric Hyp Test in the forum General 15 years ago

    It depends – what is driving your non-normality – skewness, bimodal, outliers?
    If the data is symmetric or moderately slewed and n for each sample is > 15 central limit theorem will give you approximate validity.
    You can also try a box-cox transformation. If you find a suitable transformation, the same transformation must be applied to both…[Read more]

  • John Noguera replied to the topic Nonparametric Hyp Test in the forum General 15 years ago

    Retract – use two sample t with unequal variance. 

  • John Noguera replied to the topic Nonparametric Hyp Test in the forum General 15 years ago

    Use Welch’s ANOVA ( Assuming that your sample size is large enough for Central Limit Theorem to work).  JMP and SigmaXL include this tool.

  • Geckho,
    It is an interesting discussion.  I do appreciate your answer, but I believe that if you look at the work done by people who have dedicated their careers to best practices in SPC (e.g. Donald Wheeler) you will find a consistent theme: Do not recalculate established limits unless you have deliberately improved/changed the process.
    I…[Read more]

  • Gekho,
    Sorry I did not properly answer your 3rd question.  It was a moving window but I am not sure of the window size. 
     

  • Geckho,
    No problem.   See answers below.
    Was it an automated SPC system? Yes.
    Was there an actual person looking at the data, or was it all recorded, analyzed, and controlled by the equipment? There was an owner of the data, but this person incorrectly assumed that they would be alerted whenever there was a problem.
    Were they recalculating u…[Read more]

  • Dave,
    Thanks for your reply.  The issue I have here is  the default of automatic recalculation of limits when the “Update Graph Automatically” is turned on.  You should set the default to continue using existing limits (and provide an optional auto-recalculate).
    This is a matter of poka-yoke not training.  For example you do this very well in…[Read more]

  • Darth is correct.  Automatic recalculation of control limits is wrong.  I have personally seen a semiconductor supply company use automatic recalculation to their detriment.  There was a slow long term drift over a one year period of time. They totally missed it because spc alarms thafailed to trigger due to the automatic recalculation of limits…[Read more]

  • John Noguera replied to the topic ANOVA Assumption in the forum General 15 years, 5 months ago

    In this case there is a better alternative to Kruskal-Wallis or Mood’s Median. It is called Welch’s ANOVA currently only available in JMP, but soon to be included in another tool. 

  • Load More