Mayank Gupta

Srilaxmi has provided the best answer to the question by highlighting the multiple uses of Percentile. Additionally, Saurabh has summarized the differences well in a table. Review his answer as well.

All the published answers are correct. Srilaxmi has provided the most comprehensive answer highlighting the multiple challenges of FGD and its usage in DMAIC project. Hence, her answer has been selected as the best.

While all published answers are correct. Sriya has provided the most comprehensive and complete answer and hence has been declared as the winner.

Sriya has provided the best answer to this question. Well done!

Sriya has provided the best answer to the question with a suitable example. Answer from Rahul is also a must read.

Rahul Ganapathy has provided the best answer to the question. Other answers are also a must read.

Great answers from all respondents. It was difficult to zero in on the winner, however, Aarti has provided the best answer to the question. Do read answers from Rahul and Sriya.

Sriya has provided the best answer to the question. Other answers are also worth reading.

While the published answers have explained and compared both project charter and BOSCARD, the comparison would have come out better with an example which sadly no one has added. Hence there is no winner for this question. Dhruva's answer highlights the advantages of one over the other while Adil's answer compares the two in a tabular format. Do read them.

Saurabh has given the best answer to the question. Well done!

Most of the respondents have answered it correctly. Pareto is used as a prioritization tool i.e. to focus on the critical areas which when worked upon have a potential to give a big benefit. Adil Khan has given the best answer to the question. Also read the answer from Aarti. She has highlighted areas where Pareto cannot be used.

Few of the answers to this question could not be approved as they either failed in AI generated content or in plagiarism. From the published answers, unfortunately none of them provide the correct answer, hence there is no winner to this question. R-sq or R-sq (adj) value of 1 is practically impossible to get as there will always be some variation in the observed data points while there will be no such variation in the predicted value (calculated from the equation).

This was a tricky one. And as expected, some of you missed the trick. Process improvements are needed when specification limits get revised, however the question was opposite. Do process improvements result in a change in specification limits? Generally speaking, process improvements result in a change in the control limits, however there are instances where process improvements also result in a change in the specification limits. This is particularly true when the specification limits are decided by the business, R&D or market. And then there are also instances where regulators and customers play the catch up game The best answer to this question is provided by R Rajesh. Answers from Adil Khan, Aarti T, Keerthi Vasan are also a must read.

Saurabh Narkar has given the best answer to the question by providing an example of risk reduction leading to RPN of 1. Answers from Adil Khan and Keerthi Vasan are also a must read.

The snapshot is comprehensive. Highlights initiative is currently not active.

Keerthi Vasan has given the best answer to the question.

Very interesting answers and examples quoted. The best answer was provided by Adil Khan and hence his answer has been selected as the winner. R Rajesh also mentions a very important point that if a process step has an RPN of 1000, there will definitely be some mitigation actions that will be taken to reduce the risk at the particular step.

The question was for variables that are in known cause and effect relationship. While, some of the answers have highlighted cases where correlation is zero but that is between two unrelated things. Correlation coefficient can be zero between 2 variables (that in a known cause and effect relationship) if they have a non-linear relationship. The best answer has been provided by Keerthi Vasan. Well done!

Glad that most respondents answered correctly. The best answer has been given by Keerthi Vasan. Well done!

All the answers are very interesting. Some of the examples quoted for perfect correlation uses well established formulae, where of course there is only 1 input variable (e.g. perimeter of a square), but again the fact is that in real life there is hardly any situation where there will be only 1 factor affecting the output. Plus it was correctly identified that there will be some measurement system errors while measuring the length of the perfect square. There are also a few answers where we have forgotten to check for X and Y variables (e.g. Temp conversion). Yes, correlation can be done between any 2 variables, however it will not be meaningful. Read more about it at the below link https://www.benchmarksixsigma.com/forum/topic/35495-correlation-and-causation/ The best answer has been provided by Adil Khan. Well done!

Adil Khan has given the best answer to the question by highlighting the challenges in each of the approaches and the industries where it suits best. Do read all the answers to get varied examples of organizations where the two techniques are used.

Interesting thoughts from the respondents. Adil Khan has provided the most appropriate answer to the question and hence has been selected as the winner. Do read Ramdas Jadhav's answer as he provides a very interesting and a different view (contrary to the popular believe).

This question has thrown up surprises. It seemed easy but still there are a few answers that have not been approved because they were incorrect. There are also a couple of answers that were not approved due to AI generated content. Anyway, lets come to this question, the remaining answer from Adil Khan has been selected the best answer. However, want to add a few points 1. Looking alone at Pp (or Cp) is detrimental for two reasons It does not consider the process centricity It cannot be calculated for single side specifications 2. Some experienced practitioners only look at Ppk (or Cpk) value. since Ppk value will always be less than equal to Pp, therefore they work with a criteria of Ppk to be greater or equal to 1.33 (the number 1.33 could be different for some industries). This will ensure that Pp value is also acceptable. Keep in mind that process might still be off centered but is still capable of meeting customer specifications.

Consider the practical significance of rejecting the Null Hypothesis. If rejecting Ho results in practical gains in the process, then by all means reject it. Paired T test is statistically more powerful as compared to 2 sample T test, provided the external conditions are same. If the processing was done by same agent and on the same transaction (in context of service industry), then we can do the Paired T test. If the agents or transactions were different then 2 sample T test is a better option.

A lot of answers were dis-approved either due to high % of AI generated content or high plagiarism. Among the published answers, Keerthi Vasan has given the best answer.