• More of my philosophy about the Post Graduate Program on lean Six Sigma

    From World-News2100@21:1/5 to All on Wed Feb 16 20:52:23 2022
    Hello,


    More of my philosophy about the Post Graduate Program on lean Six Sigma
    and more..

    I am a white arab, and i think i am smart since i have also
    invented many scalable algorithms and algorithms..


    I think i am really smart and i invite you to read carefully the
    following webpage of Alan Robinson Professor of Operations Management at University of Massachusetts and that is a full-time professor at the
    Isenberg School of Management of UMass and a consultant and book author specializing in managing ideas (idea-generation and idea-driven
    organization) and building high-performance organizations, creativity, innovation, quality, and lean management:

    https://www.simplilearn.com/pgp-lean-six-sigma-certification-training-course?utm_source=google&utm_medium=cpc&utm_term=&utm_content=11174393172-108220153863-506962883161&utm_device=c&utm_campaign=Display-MQL-DigitalOperationsCluster-PG-QM-CLSS-UMass-
    YTVideoInstreamCustomIntent-US-Main-AllDevice-adgroup-QM-Desktop-CI&gclid=Cj0KCQiA3rKQBhCNARIsACUEW_ZGLHcUP2htLdQo46zP6Eo2-vX0MQYvc-o6GQP55638Up4tex85RBEaArn9EALw_wcB


    And notice in the above webpage of the professor, that he is giving Post Graduate Program in Lean Six Sigma and on agile methodology, and i think
    that this Post Graduate Program is easy for me since i am really smart
    and i can easily understand lean Six Sigma or Six Sigma and i can easily understand agile methodology, and notice that i am in my below thoughts
    also explaining much more smartly what is agile methodology, and i think
    that the more difficult part of Six Sigma or lean Six Sigma is to
    understand the central limit theorem and to understand what is
    SPC(Statistical quality control) and how to use the control charts so
    that to control the variability of the defects, and notice that i am
    talking about it in my below thoughts, but i think that the rest of lean
    Six Sigma and Six Sigma is easy for me.

    More of my philosophy about Six Sigma and more..

    I think i am really smart, and now i will talk more about Six Sigma
    since i have just talked about SPC(Statistical quality control), so
    you have to know that Six Sigma needs to fulfill the following steps:

    1- Define the project goals and customer (external and internal)
    deliverables.

    2- Control future performance so improved process doesn't degrade.

    3- Measure the process so that to determine current performance and
    quantify the problem.

    4- Analyze and determine the root cause(s) of the defects.

    5- Improve the process by eliminating the defects.


    And you have to know that those steps are also important steps toward
    attaining ISO 9000 certification, and notice that you can use
    SPC(Statistical process control) and the control charts on step [4] and
    step [5] above.

    Other than that i have just read the following interesting important
    paper about SPC(Statistical process control) that explains all the
    process of SPC(Statistical process control), so i invite you to read it carefully:

    https://owic.oregonstate.edu/sites/default/files/pubs/EM8733.pdf

    So as you notice in the above paper that the central limit theorem
    in mathematics is so important, but notice carefully that the necessary
    and important condition so that the central limit theorem works is that
    you have to use independent and random variables, and notice in the
    above paper that you have to do two things and it's that you have to
    reduce or eliminate the defects and you have to control the
    "variability" of the defects, and this is why the paper is talking about
    how to construct a control chart. Other than that the central limit
    theorem is not only related to SPC(Statistical process control), but it
    is also related to PERT and my PERT++ software project below, and notice
    that in my software project below that is called PERT++, i have provided
    you with two ways of how to estimate the critical path, first, by the
    way of CPM(Critical Path Method) that shows all the arcs of the estimate
    of the critical path, and the second way is by the way of the central
    limit theorem by using the inverse normal distribution function, and you
    have to provide my software project that is called PERT++ with three
    types of estimates that are the following:

    Optimistic time - generally the shortest time in which the activity
    can be completed. It is common practice to specify optimistic times
    to be three standard deviations from the mean so that there is
    approximately a 1% chance that the activity will be completed within
    the optimistic time.

    Most likely time - the completion time having the highest
    probability. Note that this time is different from the expected time.

    Pessimistic time - the longest time that an activity might require.
    Three standard deviations from the mean is commonly used for the
    pessimistic time.


    And you can download my PERT++ from reading my following below thoughts:

    More of my philosophy about the central limit theorem and about my
    PERT++ and more..

    The central limit theorem states that the sampling distribution of the
    mean of any independent, random variable will be normal or nearly
    normal, if the sample size is large enough.

    How large is "large enough"?

    In practice, some statisticians say that a sample size of 30 is large
    enough when the population distribution is roughly bell-shaped. Others recommend a sample size of at least 40. But if the original population
    is distinctly not normal (e.g., is badly skewed, has multiple peaks,
    and/or has outliers), researchers like the sample size to be even
    larger. So i invite you to read my following thoughts about my software
    project that is called PERT++, and notice that the PERT networks are
    referred to by some researchers as "probabilistic activity networks"
    (PAN) because the duration of some or all of the arcs are independent
    random variables with known probability distribution functions, and have
    finite ranges. So PERT uses the central limit theorem (CLT) to find the expected project duration.

    And as you are noticing this Central Limit Theorem is also so important
    for quality control, read the following to notice it(I also understood Statistical Process Control (SPC)):

    An Introduction to Statistical Process Control (SPC)

    https://www.engineering.com/AdvancedManufacturing/ArticleID/19494/An-Introduction-to-Statistical-Process-Control-SPC.aspx

    Also PERT networks are referred to by some researchers as "probabilistic activity networks" (PAN) because the duration of some or all of the arcs
    are independent random variables with known probability distribution
    functions, and have finite ranges. So PERT uses the central limit
    theorem (CLT) to find the expected project duration.

    So, i have designed and implemented my PERT++ that that is important for quality, please read about it and download it from my website here:

    https://sites.google.com/site/scalable68/pert-an-enhanced-edition-of-the-program-or-project-evaluation-and-review-technique-that-includes-statistical-pert-in-delphi-and-freepascal

    ---


    So I have provided you in my PERT++ with the following functions:


    function NormalDistA (const Mean, StdDev, AVal, BVal: Extended): Single;

    function NormalDistP (const Mean, StdDev, AVal: Extended): Single;

    function InvNormalDist(const Mean, StdDev, PVal: Extended; const Less: Boolean): Extended;

    For NormalDistA() or NormalDistP(), you pass the best estimate of
    completion time to Mean, and you pass the critical path standard
    deviation to StdDev, and you will get the probability of the value Aval
    or the probability between the values of Aval and Bval.

    For InvNormalDist(), you pass the best estimate of completion time to
    Mean, and you pass the critical path standard deviation to StdDev, and
    you will get the length of the critical path of the probability PVal,
    and when Less is TRUE, you will obtain a cumulative distribution.


    So as you are noticing from my above thoughts that since PERT networks
    are referred to by some researchers as "probabilistic activity networks"
    (PAN) b
  • From World-News2100@21:1/5 to All on Tue Mar 1 12:29:46 2022
    Hello,


    More of my philosophy about the Post Graduate Program on lean Six Sigma
    and more..

    I am a white arab, and i think i am smart since i have also
    invented many scalable algorithms and algorithms..


    More of my philosophy about Six Sigma and more..

    I think i am smart, and now i will talk more about Six Sigma
    since i have just talked about SPC(Statistical quality control), so
    you have to know that Six Sigma needs to fulfill the following steps:

    1- Define the project goals and customer (external and internal)
    deliverables.

    2- Control future performance so improved process doesn't degrade.

    3- Measure the process so that to determine current performance and
    quantify the problem.

    4- Analyze and determine the root cause(s) of the defects.

    5- Improve the process by eliminating the defects.


    And you have to know that those steps are also important steps toward
    attaining ISO 9000 certification, and notice that you can use
    SPC(Statistical process control) and the control charts on step [4] and
    step [5] above.

    Other than that i have just read the following interesting important
    paper about SPC(Statistical process control) that explains all the
    process of SPC(Statistical process control), so i invite you to read it carefully:

    https://owic.oregonstate.edu/sites/default/files/pubs/EM8733.pdf

    So as you notice in the above paper that the central limit theorem
    in mathematics is so important, but notice carefully that the necessary
    and important condition so that the central limit theorem works is that
    you have to use independent and random variables, and notice in the
    above paper that you have to do two things and it's that you have to
    reduce or eliminate the defects and you have to control the
    "variability" of the defects, and this is why the paper is talking about
    how to construct a control chart. Other than that the central limit
    theorem is not only related to SPC(Statistical process control), but it
    is also related to PERT and my PERT++ software project below, and notice
    that in my software project below that is called PERT++, i have provided
    you with two ways of how to estimate the critical path, first, by the
    way of CPM(Critical Path Method) that shows all the arcs of the estimate
    of the critical path, and the second way is by the way of the central
    limit theorem by using the inverse normal distribution function, and you
    have to provide my software project that is called PERT++ with three
    types of estimates that are the following:

    Optimistic time - generally the shortest time in which the activity
    can be completed. It is common practice to specify optimistic times
    to be three standard deviations from the mean so that there is
    approximately a 1% chance that the activity will be completed within
    the optimistic time.

    Most likely time - the completion time having the highest
    probability. Note that this time is different from the expected time.

    Pessimistic time - the longest time that an activity might require.
    Three standard deviations from the mean is commonly used for the
    pessimistic time.

    And you can download my PERT++ from reading my following below thoughts:

    More of my philosophy about the central limit theorem and about my
    PERT++ and more..

    The central limit theorem states that the sampling distribution of the
    mean of any independent, random variable will be normal or nearly
    normal, if the sample size is large enough.

    How large is "large enough"?

    In practice, some statisticians say that a sample size of 30 is large
    enough when the population distribution is roughly bell-shaped. Others recommend a sample size of at least 40. But if the original population
    is distinctly not normal (e.g., is badly skewed, has multiple peaks,
    and/or has outliers), researchers like the sample size to be even
    larger. So i invite you to read my following thoughts about my software
    project that is called PERT++, and notice that the PERT networks are
    referred to by some researchers as "probabilistic activity networks"
    (PAN) because the duration of some or all of the arcs are independent
    random variables with known probability distribution functions, and have
    finite ranges. So PERT uses the central limit theorem (CLT) to find the expected project duration.

    And as you are noticing this Central Limit Theorem is also so important
    for quality control, read the following to notice it(I also understood Statistical Process Control (SPC)):

    An Introduction to Statistical Process Control (SPC)

    https://www.engineering.com/AdvancedManufacturing/ArticleID/19494/An-Introduction-to-Statistical-Process-Control-SPC.aspx

    Also PERT networks are referred to by some researchers as "probabilistic activity networks" (PAN) because the duration of some or all of the arcs
    are independent random variables with known probability distribution
    functions, and have finite ranges. So PERT uses the central limit
    theorem (CLT) to find the expected project duration.

    So, i have designed and implemented my PERT++ that that is important for quality, please read about it and download it from my website here:

    https://sites.google.com/site/scalable68/pert-an-enhanced-edition-of-the-program-or-project-evaluation-and-review-technique-that-includes-statistical-pert-in-delphi-and-freepascal

    ---


    So I have provided you in my PERT++ with the following functions:


    function NormalDistA (const Mean, StdDev, AVal, BVal: Extended): Single;

    function NormalDistP (const Mean, StdDev, AVal: Extended): Single;

    function InvNormalDist(const Mean, StdDev, PVal: Extended; const Less: Boolean): Extended;

    For NormalDistA() or NormalDistP(), you pass the best estimate of
    completion time to Mean, and you pass the critical path standard
    deviation to StdDev, and you will get the probability of the value Aval
    or the probability between the values of Aval and Bval.

    For InvNormalDist(), you pass the best estimate of completion time to
    Mean, and you pass the critical path standard deviation to StdDev, and
    you will get the length of the critical path of the probability PVal,
    and when Less is TRUE, you will obtain a cumulative distribution.


    So as you are noticing from my above thoughts that since PERT networks
    are referred to by some researchers as "probabilistic activity networks"
    (PAN) b
  • From World-News2100@21:1/5 to All on Mon Mar 7 16:24:46 2022
    Hello,


    More of my philosophy about the Post Graduate Program on lean Six Sigma
    and more..

    I am a white arab, and i think i am smart since i have also
    invented many scalable algorithms and algorithms..


    More of my philosophy about Six Sigma and more..

    I think i am smart, and now i will talk more about Six Sigma
    since i have just talked about SPC(Statistical quality control), so
    you have to know that Six Sigma needs to fulfill the following steps:

    1- Define the project goals and customer (external and internal)
    deliverables.

    2- Control future performance so improved process doesn't degrade.

    3- Measure the process so that to determine current performance and
    quantify the problem.

    4- Analyze and determine the root cause(s) of the defects.

    5- Improve the process by eliminating the defects.


    And you have to know that those steps are also important steps toward
    attaining ISO 9000 certification, and notice that you can use
    SPC(Statistical process control) and the control charts on step [4] and
    step [5] above.

    Other than that i have just read the following interesting important
    paper about SPC(Statistical process control) that explains all the
    process of SPC(Statistical process control), so i invite you to read it carefully:

    https://owic.oregonstate.edu/sites/default/files/pubs/EM8733.pdf

    So as you notice in the above paper that the central limit theorem
    in mathematics is so important, but notice carefully that the necessary
    and important condition so that the central limit theorem works is that
    you have to use independent and random variables, and notice in the
    above paper that you have to do two things and it's that you have to
    reduce or eliminate the defects and you have to control the
    "variability" of the defects, and this is why the paper is talking about
    how to construct a control chart. Other than that the central limit
    theorem is not only related to SPC(Statistical process control), but it
    is also related to PERT and my PERT++ software project below, and notice
    that in my software project below that is called PERT++, i have provided
    you with two ways of how to estimate the critical path, first, by the
    way of CPM(Critical Path Method) that shows all the arcs of the estimate
    of the critical path, and the second way is by the way of the central
    limit theorem by using the inverse normal distribution function, and you
    have to provide my software project that is called PERT++ with three
    types of estimates that are the following:

    Optimistic time - generally the shortest time in which the activity
    can be completed. It is common practice to specify optimistic times
    to be three standard deviations from the mean so that there is
    approximately a 1% chance that the activity will be completed within
    the optimistic time.

    Most likely time - the completion time having the highest
    probability. Note that this time is different from the expected time.

    Pessimistic time - the longest time that an activity might require.
    Three standard deviations from the mean is commonly used for the
    pessimistic time.

    And you can download my PERT++ from reading my following below thoughts:

    More of my philosophy about the central limit theorem and about my
    PERT++ and more..

    The central limit theorem states that the sampling distribution of the
    mean of any independent, random variable will be normal or nearly
    normal, if the sample size is large enough.

    How large is "large enough"?

    In practice, some statisticians say that a sample size of 30 is large
    enough when the population distribution is roughly bell-shaped. Others recommend a sample size of at least 40. But if the original population
    is distinctly not normal (e.g., is badly skewed, has multiple peaks,
    and/or has outliers), researchers like the sample size to be even
    larger. So i invite you to read my following thoughts about my software
    project that is called PERT++, and notice that the PERT networks are
    referred to by some researchers as "probabilistic activity networks"
    (PAN) because the duration of some or all of the arcs are independent
    random variables with known probability distribution functions, and have
    finite ranges. So PERT uses the central limit theorem (CLT) to find the expected project duration.

    And as you are noticing this Central Limit Theorem is also so important
    for quality control, read the following to notice it(I also understood Statistical Process Control (SPC)):

    An Introduction to Statistical Process Control (SPC)

    https://www.engineering.com/AdvancedManufacturing/ArticleID/19494/An-Introduction-to-Statistical-Process-Control-SPC.aspx

    Also PERT networks are referred to by some researchers as "probabilistic activity networks" (PAN) because the duration of some or all of the arcs
    are independent random variables with known probability distribution
    functions, and have finite ranges. So PERT uses the central limit
    theorem (CLT) to find the expected project duration.

    So, i have designed and implemented my PERT++ that that is important for quality, please read about it and download it from my website here:

    https://sites.google.com/site/scalable68/pert-an-enhanced-edition-of-the-program-or-project-evaluation-and-review-technique-that-includes-statistical-pert-in-delphi-and-freepascal

    ---


    So I have provided you in my PERT++ with the following functions:


    function NormalDistA (const Mean, StdDev, AVal, BVal: Extended): Single;

    function NormalDistP (const Mean, StdDev, AVal: Extended): Single;

    function InvNormalDist(const Mean, StdDev, PVal: Extended; const Less: Boolean): Extended;

    For NormalDistA() or NormalDistP(), you pass the best estimate of
    completion time to Mean, and you pass the critical path standard
    deviation to StdDev, and you will get the probability of the value Aval
    or the probability between the values of Aval and Bval.

    For InvNormalDist(), you pass the best estimate of completion time to
    Mean, and you pass the critical path standard deviation to StdDev, and
    you will get the length of the critical path of the probability PVal,
    and when Less is TRUE, you will obtain a cumulative distribution.


    So as you are noticing from my above thoughts that since PERT networks
    are referred to by some researchers as "probabilistic activity networks"
    (PAN) b