navin.rohilla

Hi Radhika, Although most of the steps are cleared by SJ, I would suggest to you to go for Time and motion study also to find out the time wasted in Non value added things also. Regards Navin Rohilla BB

Box cox takes your data away from reality and Johnson also takes your data more away then the Box cox transformation hence for better Analysis, Box cox transformation is better then Johnson. When Box cox some times fails to convert the data to normal,due to lamda value or if the data value is less then 1 or in negative or any other cause. so we can use Johnson transformation in these cases. so johnson transformation is stroger to transform non normal to normal but gives poor to evaluate analysis. so first choice is Box cox if it fails then go for Johnson transformation But as said earlier would suggest you to not use any of the tranformation go for alternative tests. Transformation makes your analysis very complicated. Navin Rohilla BB Max New york Life

Dear Faisal, Your question gives no conclusion and clue of the data type of 50 readings if the data type is contineous go for normality test if it fails go for non parametic test rather then transformation. CAUTION: Only do transformation when mbb suggest . It can create lot of complication in data analysis in later stage.(Box cox is stronger and better transformation. if box cox fails then only go for johnson transformation.) Suggesting to not to go for transformation untill and unless you are expert Regards Navin Rohilla BB

SJ has suggest correctly pareto is a principle not a law. It may be applicable in your data or it may not be applicable in data. We need to do proper statification for x's if pareto principle fails Regards Navin Rohilla BB

Dear Niranjan, First check the theoritcally that the data is dicrete or contineus , Then check the behaviour of the data based on distribution If data is contineus as per defination(theoritically), it should folllow normal distribution if not then use non parametrica test . there is no need to check other distribution pattern like binomial and poisson distribution(Which are exclusively for discrete). If the data is discrete theoritically, and behaves like discrete then check binomial (if the ans is yes or no format) and for ordinal data check for poisson distribution. ALWAYS TAKE CARE OF CLT BEFORE CONCLUDING ORDINAL DATA HAS DISCRETE OR CONTINEOUS BEHAVIOUR. USE DIFFERENT TOOLS FOR DISCRETE AND CONTINEUS AS PER THERE DISTRIBUTION BEHAVIOR regards Navin Rohilla BB

Dear All, Debate on Discrete and Contineous is more older than six sigma, In most of the cases when data is in % then the people starts getting confused. Here is the golden rule to decide data type in proportion data. discrete numerator, contineus denominator = contineus is the data contineous numerator and contineus denominator = contineus is the data discrete numeratior and discrete denominator = data is discrete Contineus numerator and discrete denominator = data is contineus In proportion cases numerator decides the fate of the data type. Thease are the theoritical explanation of data type. Practically, Discrete data may behave like contineous as per CL theorum or due to incorrect data collecion or msa error. if no msa error then Contineus data may behave like discrete due to biologican or mechanical life of data Work with data and select the tools for data as per there distribution behviour not as per there theoritical definations I hope it will help Navin Rohilla BB

Hi All, In the Modern era , the new concept of Quality is to reduce the cost with improve in Quality (Customer satisfaction) simulateously. Both are like romeo and juliat. if you will prioritize cost reduction only and do not measure as a secondary matrix cutomer satisfaction . It means you are providing solution for cost reduction at the cost of low customer satisfaction. So both primary and secondary ctq should be measured simulataneously. Increase in cust satisfaction with more cost makes no sense Reduction in cost with redution in customer satisfaction also makes no sense. ONLY WIN WIN CASE IS REDUCTION IN COST WITH IMPROVE IN CUSTOMER SATISFACTION. I hope this will help Navin Rohilla BB