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  • THE OPEN QUESTION on the forum right now is on Cohen's Kappa vs Fleiss KappaThis is part of our TWO QUESTIONS PER WEEK initiative. One question is launched on Tuesday and the other on Friday, both at 5 PM IST. Best answers are recognized well on this most active Lean Six Sigma forum. (Benchmark Six Sigma Forum ranks first on Google Search based on popularity) 

     

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  • ALL TIME GB TOP SCORERS

     

    Name

    Score (%)

    City/Year

     
     

    Purvi Gupta

    100

    Del 2019

     

    Bhawana Sethi

    100

    Del 2015

     

    Adyan Prabhakaran

    100

    Hyd 2014

     

    Thirumoorthi.M

    99

    Chn 2019

     

    Sneha Vivek More

    99

    Mum 2019

     

    Sumita Maiti

    99

    Kol 2017

     

    Vidula Valavalkar

    99

    Hyd 2014

     

    Vishal Tillu

    99

    Mum 2014

     

    Yashwanth J G

    99

    Bng 2013

     

    Jyothi Kanuri

    99

    Hyd 2013

     

    Vrajesh Parekh

    99

    Mum 2013

     

    Gnanasekaran D

    99

    Chn 2012

     

    Benoy Ramachandran

    99

    Chn 2012

     

     

    Muthu Naveen S

    99

    Mum 2012

     

    Ketan Trivedi

    99

    Mum 2012

     

    Piyush Mangal

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    Del 2011

     

    Sourav Thakur

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    Del 2011

     

    Tushar Chaudhari

    99

    Mum 2011

     

    Komal Bansal

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    Parag Suresh Kamble

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    Ritik Gupta

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    Pun 2011

     

    Amit Kumar Makkar

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    Del 2010

     

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    Del 2010

     

    Clarence Wong

    99

    Hyd 2010

     

    Devendra Singh Baghel

    99

    Hyd 2010

     

    Varun Hemrajani

    99

    Pun 2010

     
         

    Here is the complete list of all time Lean Six Sigma Green Belt Top Scorers

  • ALL TIME BB TOP SCORERS

     

    Name

    Score (%)

    City/Year

     
     

    Kunal Obhrai

    98

    Del 2019

     

    Mahesh P K

    98

    Bng 2017

     

    Balaji M

    97

    Bng 2017

     

    Rohit Arora

    97

    Bng 2017

     

    Amit Kumar Makkar

    97

    Del 2015

     

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    Del 2013

     

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    97

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    97

    Hyd 2011

     

    Ashish Sharma

    96

    Pun 2019

     

    Sunil M. Bhat

    96

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    96

    Del 2017

     

    Apoorve Arya

    96

    Mum 2014

     

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    96

    Chn 2013

     

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    95

    Mum 2020

     

    Zeshan Abubacker

    95

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    Kumar Kaushal

    95

    Del 2019

     

    Vishal Kanojia

    95

    Hyd 2019

     

    Swati Malhotra

    95

    Mum 2019

     

    Nithin Sandhyala

    95

    Bng 2017

     

    Abhishek Arora

    95

    Del 2017

     

    Satishkumar Jain

    95

    Mum 2017

     

    Atirakshit Bhatt

    95

    Mum 2017

     

    Narendra Anil Murdeshwar

    95

    Pun 2017

     

    Rupinder Kaur Narang

    95

    Del 2016

     

    S Sujay Kumar

    95

    Mum 2016

     

    Kuljinder Kaur

    95

    Del 2015

     

    Vetrivendhan K P

    95

    Bng 2014

     

    Sunil Bissa

    95

    Chn 2013

     

    Mayank Gupta

    95

    Pun 2011

     

    Here is the complete list of all time Lean Six Sigma Black Belt Top Scorers

  • Posts

    • There were many answers to this question. However, not all were published as some of them were incorrect. The question was a tricky one as it dealt with 2 confusing MSA methods - Attribute Agreement Analysis and Attribute Gage Study.  Attribute Agreement Analysis is used for discrete data to check for operator agreements on the attributes (there is no gauge being used here). Attribute Gage Study is used when attribute data (like Go/No Go etc.) is being generated using a gauge.  The chosen best answer is from Balaji Loganathan. Do review the response from Mr Venugopal R, Benchmark Six Sigma's in-house expert.
    • Q 536. Minitab has the ability to report 2 different Kappa values for Attribute Agreement Analysis - Cohen's Kappa and Fleiss Kappa. What is the difference between the two? Using an example highlight the situation where a researcher will look at Cohen's Kappa instead of Fleiss Kappa.   Note for website visitors - Two questions are asked every week on this platform. One on Tuesday and the other on Friday.  All questions so far can be seen here - https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/ Please visit the forum home page at https://www.benchmarksixsigma.com/forum/ to respond to the latest question open till the next Tuesday/ Friday evening 5 PM as per Indian Standard Time. Questions launched on Tuesdays are open till Friday and questions launched on Friday are open till Tuesday. When you respond to this question, your answer will not be visible till it is reviewed. Only non-plagiarised (plagiarism below 5-10%) responses will be approved. If you have doubts about plagiarism, please check your answer with a plagiarism checker tool like https://smallseotools.com/plagiarism-checker/ before submitting.  The best answer is always shown at the top among responses and the author finds honorable mention in our Business Excellence dictionary at https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term
    • Benchmark Six Sigma Expert View by Venugopal R ATTRIBUTE AGREEMENT ANALYSIS (AAA) is a method of performing MSA (Measurement Systems Analysis). MSA is done to assess reliability of Measurement Systems. When we have an attribute type of measurement;  for example – visual inspection, manual validation of insurance claims, document classification etc., where the decisions are based on human (Appraiser) judgement, and no measuring instrument is involved – the outcome will be categorical (Example – Pass/Fail, Accept/Reject, Good/Bad etc.). For such measurement systems, we can use the Attribute Agreement Analysis to evaluate the acceptability of the system.   The AAA helps to evaluate the extent of agreement 'within appraisers', 'between appraisers', 'the accuracy of appraisers' and the 'overall measurement system’s accuracy'.     The Attribute Agreement Analysis is capable of giving 4 outputs, viz. 1.       Within Appraiser variation (Repeatability) 2.       Between Appraiser variation (Reproducibility) 3.       Appraiser vs Standard variation (Appraiser Accuracy) 4.       Overall accuracy (Team Accuracy) Point nos. 3 and 4 as above will be possible if we use a ‘Master Standard’ for comparing the decisions made by the Appraisers.   For example, if Medical Insurance Claims are processed and the acceptability of each claim is judged by few auditors, the AAA would be good method to assess the reliability of the Audit Quality   ATTRIBUTE GAGE STUDY is also an MSA methodology, and used to evaluate an attribute measurement system that uses an attribute gauge, which only screens the acceptable and non-acceptable parts, though the parts will have a value for the measured parameter.   Attribute Gage Study examines the bias and repeatability of the system. For example, if an air plug gauge is used as a ‘go – no go’ measurement for diameter, the Attribute GageSstudy can be performed to assess the bias and repeatability of the system. For performing the Attribute Gage Study, a few parts are selected such that the range of their dimensions represent the normal operating range. Each part should have a reference value, which is the known and correct value for that part. Each part must be measured repeatedly for multiple times (recommended 20 times) and the number of ‘Accepts’ and ‘Rejects’ need to be recorded.   Detailed requirements for the parts are given by AIAG’s MSA reference manual.   The Attribute Gage Study report will contain: 1.       Fitted line for ‘% acceptance vs Ref value of measured part.’ 2.       Bias (acceptability of bias is based on p-value) 3.       Repeatability 4.       Graph for Probability of acceptance vs Ref value of measured part’.
    • An investigation into the bias and consistency of an attribute measuring system is known as an attribute gauge study. A 100% end-of-line inspection, for instance, might be carried out by an automatic inspection gauge. This gauge needs to be reliable and reproducible. It is more common to refer to the study as Attribute Agreement Analysis when the performance of the gauge or technique under consideration is utilized to generate judgements on a non-continuous scale, such as Pass/Fail or a rating Nowadays, a lot of businesses conduct studies on their measuring devices using gauge R&R. Less well known are the resources that are currently available for conducting comparable studies for non-measurement type instruments, such as Go/No-Go gauges. The study of instruments that measure properties on a continuous scale, such as force, length, viscosity, pH, etc., falls under the purview of gauge research and development. It is more common to refer to the study as Attribute Agreement Analysis when the performance of the gauge or technique under consideration is utilized to generate judgements on a non-continuous scale, such as Pass/Fail or a rating.   An Attribute Agreement Analysis study is created like a regular Gage R&R study. A series of parts are selected from the process and evaluated by two or more operators. From this research, it will be possible to determine how consistent operators are in their own ratings and the degree of agreement between operators. If you can set the evaluation criteria for each part, you can also compare the performance of each operator to the criteria. Attribute agreement analysis studies are not only applicable to pass/fail ratings used in pass/fail gauges, but can also be used to test operator consistency when making ratings on rating scales. increase. Collect survey data and perform analysis using modern statistical software such as Minitab. Graphical output and statistical kappa values can be used to examine operator effectiveness and accuracy in conducting assessments.
    • An Attribute Gage study is a study that studies the bias and repeatability of an attribute measurement system. It is useful to decide which sources are responsible for the variation of the measurement data. The best one of these is a go/no go gage. This gage basically tells you if the part passes or it fails. There are only two likely outcomes. Other attribute measurement systems can have many categories such as very good, good, poor and very poor   What is an attribute agreement analysis?   Attribute Agreement Analysis (or Attribute MSA) is one of the tools within MSA, used to estimate your measurement system when attribute (qualitative) measurements are involved. With this we can confirm that measurement error is at an acceptable level before conducting data analysis   Attribute Agreement Analysis is the type of Measurement System Analysis (MSA) that is used to measure how well an attribute (discrete) measurement system is working. Gage R&R is the type of Measurement System Analysis (MSA) that is used to measure how well a variable (continuous) measurement system is working.   The Attribute Agreement Analysis study can be set up in a similar way as a regular Gauge R&R study. A number of parts are selected from the process, and are gage by two or more operators. This doesn’t just relate to Pass/Fail type assessments, such as with Go/No-Go type gauges, but it can also be used to test the reliability of operators where they make assessment on a rating scale.   When to Work with Attribute Agreement Analysis ?    Work with Attribute Agreement Analysis if you aim at doing a Gage R&R (MSA) for a test/measurement that does NOT lead to results you could gage with a measurement instrument. we want it if the results are qualitative. Examples: Visual quality control of parts. Examination of whether the cleaning was done well. Check whether a document is accessible. To Run the Analysis    What is our objective to find out? Accuracy or Precision? Reproducibility or Repeatability?    To Calculate Accuracy     Understand how well the measurement system comes to the same results as per the “standard”.   Calculate % R & R    Shows how exactly the different appraisers agree about results and how precisely one and the same appraiser comes to the same results when measuring multiple times.  Total % R&R defines the level of agreement within/ between appraisers and a standard Total %R&R should be 100% (when the study conditions are different from reality every result below 100% will lead to a measurement system not worth trusting) If the Total %R&R is less than 100% examine the results to see if this is a problem of repeatability, reproducibility or both
    • There are 2 answers that stand out - Dheeraj Bhardwaj - for explaining the two underlying plots i.e. box plot and kernel density plot Anupam Goswami - for providing insights into where Violin Plot can be used along with examples.   Both the answers have been selected as winners. Congratulations to the joint winners!
    • A Violin plot is a amalgam of a box plot and a kernel density plot that depicts peaks in the data. It is more informative than a plain box plot. A box plot only shows summary statics such as mean/median and interquartile ranges while violin plot presents the full distribution of data including density and statistics of each variable. This is very useful in cases where the data distribution is multimodal. Violin plot are useful while making a comparison of distributions between multiple groups and one can compare the peaks, valleys, and tails of each group's density curve. It intuitively shows the distribution of data in a data set. The violin plot helps in easy visualization with a viewer to understand the probability of things and therefore it is imperative for one to use a violin plot if you have a large enough dataset to capture the underlying probabilities of your dataset. But in situations where the data set is not big enough with unimodal distribution and additional information within do not add much information to show the audience which might not understand the essence of densities like in violin plot, then simple Box plot will be better suited.  
    • Q 535. What is Attribute Gage Study? How is it different from Attribute Agreement Analysis? Provide an example to highlight when will you use one over the other.   Note for website visitors - Two questions are asked every week on this platform. One on Tuesday and the other on Friday.  All questions so far can be seen here - https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/ Please visit the forum home page at https://www.benchmarksixsigma.com/forum/ to respond to the latest question open till the next Tuesday/ Friday evening 5 PM as per Indian Standard Time. Questions launched on Tuesdays are open till Friday and questions launched on Friday are open till Tuesday. When you respond to this question, your answer will not be visible till it is reviewed. Only non-plagiarised (plagiarism below 5-10%) responses will be approved. If you have doubts about plagiarism, please check your answer with a plagiarism checker tool like https://smallseotools.com/plagiarism-checker/ before submitting.  The best answer is always shown at the top among responses and the author finds honorable mention in our Business Excellence dictionary at https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term
    • A violin plot is a fusion of a box plot and a kernel density plot, which displays peaks in the data. It helps us to visualize the distribution of numerical data. Box plots can only show summary statistics, but violin plots can depict summary statistics and the density of each variable. The width of the Probability Density Function defines how often that value occurs in the data set. The wider areas of the density plot display values that occur more frequently. Violin plots are also useful in multiple distributions at once for comparison. A narrower density plot indicates values that occur less frequently. The picture below shows the shape of a data set, a violin plot can summarize a data set using five values by the following:  1.    The minimum 2.    First quartile 3.    Median 4.    Third quartile 5.    Maximum   How do you read a violin plot?   A violin plot shows how a data set varies along one variable by combining a boxplot with a Probability Density Function (PDF) the boxplot summarizes the center and spread: The white spot in the center of the box denotes the median. The length of the box indicates the (IQR) interquartile range    
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