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Q 619. R-squared (R-sq) is the most sought after number after doing Regression. While potentially R-sq can range from 0% to 100%, could there be a situation where it is 100%? Provide examples to support your answer. Note for website visitors - This platform hosts two weekly questions, one on Tuesday and the other on Friday. All previous questions can be found here: https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/. To participate in the current question, please visit the forum homepage at https://www.benchmarksixsigma.com/forum/. The question will be open until Tuesday or Friday at 5 PM Indian Standard Time, depending on the launch day. Responses will not be visible until they are reviewed, and only non-plagiarised answers with less than 5-10% plagiarism will be approved. If you are unsure about plagiarism, please check your answer using a plagiarism checker tool such as https://smallseotools.com/plagiarism-checker/ before submitting. All correct answers shall be published, and the top-rated answer will be displayed first. The author will receive an honorable mention in our Business Excellence dictionary at https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term. Some people seem to be using AI platforms to find forum answers. This is a risky approach as AI responses are error prone as our questions are application-oriented (they are never straightforward). Have a look at this funny example - https://www.benchmarksixsigma.com/forum/topic/39458-using-ai-to-respond-to-forum-questions/ We also use an AI content detector at https://crossplag.com/ai-content-detector/. Only answers with less than 15-20% AI-generated content will be approved.
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Q 660. Compare In-Sample and Out-of-Sample testing, highlighting their advantages and disadvantages. Provide examples where their use is preferred. Note for website visitors - This platform hosts two weekly questions, one on Tuesday and the other on Friday. All previous questions can be found here: https://www.benchmarksixsigma.com/forum/lean-six-sigma-business-excellence-questions/. To participate in the current question, please visit the forum homepage at https://www.benchmarksixsigma.com/forum/. The question will be open until Tuesday or Friday at 5 PM Indian Standard Time, depending on the launch day. Responses will not be visible until they are reviewed, and only non-plagiarised answers with less than 5-10% plagiarism will be approved. If you are unsure about plagiarism, please check your answer using a plagiarism checker tool such as https://smallseotools.com/plagiarism-checker/ before submitting. All correct answers shall be published, and the top-rated answer will be displayed first. The author will receive an honorable mention in our Business Excellence dictionary at https://www.benchmarksixsigma.com/forum/business-excellence-dictionary-glossary/ along with the related term. Some people seem to be using AI platforms to find forum answers. This is a risky approach as AI responses are error prone as our questions are application-oriented (they are never straightforward). Have a look at this funny example - https://www.benchmarksixsigma.com/forum/topic/39458-using-ai-to-respond-to-forum-questions/ We also use an AI content detector at https://crossplag.com/ai-content-detector/. Only answers with less than 15-20% AI-generated content will be approved. -
Q 497. What is autocorrelation in regression analysis? Why is it a problem and how can a project leader deal with it? 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
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Q 460. What is a covariate? How does covariate reduce noise in a regression model? Explain with an example. 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
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Influential Observations
Vishwadeep Khatri posted a question in We ask and you answer! The best answer wins!
Q 369. Regression analysis identifies the best fit line. However, leverage points and large residual points can influence the fitment of the line. Both put together are known as influential or unusual observations. Explain both leverage points and large residual points with examples. Why is it important to analyze these points? 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 -
Q 361. Correlation coefficient is denoted by 'r' and R Squared (coefficient of determination) is the square of 'r'. Why do we need to run a full regression analysis if the simpler correlation coefficient itself tells us about the extent of relationship between two variables? 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. 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
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Q 286. Why is multicollinearity a problem? How is it detected? What is the right course of action when it is found? Explain with an example. 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. 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
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Residual Analysis
Vishwadeep Khatri posted a question in We ask and you answer! The best answer wins!
Q 271. What is a residual in Regression? Why is it important to analyze the residuals before assessing the goodness of a Regression Model? What does it mean if Residuals are non normal or non random? 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. 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 -
Quantile Regression
Vishwadeep Khatri posted a question in We ask and you answer! The best answer wins!
Q 232. Quantile Regression estimates the median (or a particular quantile) whereas Linear Regression estimates the mean. What are some of the business scenarios where quantile regression would yield better results as compared to linear regression? 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 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 -
What are the key differences between Multiple Regression using historical data and Multiple Regression based on Experimental Data (DOE)? What are the advantages of one over the other, if at all?
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Q. 145 What is the usage of R Squared and R Squared Adjusted as used in Regression Analysis. Please explain with example(s). 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 as per Indian Standard Time. 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.
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i am doing ordinal logistic regression using minitab, please find the results as below. when i asked my friend to cross check the results in "R" for the same data set, i was surprised to see different results come up. what was even more peculiar is that the coef no's seem to be similar however Minitab was showing -ve values where "R" was throwing +ve values and vice versa. i am curious to know why this happens and which result should i consider? Coedf(Minitab) Coef( r ) overall Rating -2.86% 2.86% Parameter (A) 1.30% -1.30% Parameter ( 9.24% -9.24% Parameter © 7.11% -7.16% Parameter(D) 6.79% -6.79% Raw data as below..( overall rating = Y, Parameters(A,B,C,D,E)=X's) Rating Scale of (1-5), 1 being lowest, 5 being highest Overall Rating Parameter(A) Parameter( Parameter( C ) Parameter (D) Parameter ( E ) 2 4 1 5 4 5 2 3 3 4 1 2 3 1 2 5 1 2 5 5 1 4 5 2 4 2 3 4 2 5 5 2 2 3 5 4 1 5 5 4 4 3 2 1 5 1 2 5 1 4 2 4 1 4 4 1 3 4 4 1 2 2 1 3 1 4 1 5 3 4 5 4 4 5 5 2 5 4 3 1 1 2 5 5 4 2 1 2 3 5 5 5 3 1 3 5 5 4 1 2 4 3 2 5 3 2 3 2 3 3 2 2 3 4 1 3 2 5 2 3 1 3 1 5 4 5 3 2 2 4 3 2 5 2 2 4 1 5 4 3 1 1 1 4 3 3 4 1 1 4 2 5 4 3 3 5 3 5 4 2 2 3 4 5 1 3 1 3 5 1 1 4 4 3 5 5 2 2 4 5 5 5 5 4 2 2 4 1 5 1 3 3 3 2 3 3 2 2 3 5 3 1 5 4 1 1 1 2 4 5 5 4 1 2 4 1 1 5 5 5 5 4 5 2 5 3 3 1 5 5 4 5 2 3 5 2 5 4 3 3 4 2 1 3 3 4 4 1 5 2 3 3 2 4 5 3 5 4 5 4 2 1 1 2 3 2 4 4 2 5 4 2 1 5 1 5 5 2 1 5 1 5 2 3 3 2 3 5 1 3 2 4 4 3 1 1 2 3 4 2 1 3 3 1 3 5 2 2 5 2 3 5 2 3 5 5 3 4 2 2 1 1 4 5 5 2 4 1 2 3 1 5 5 2 1 4 1 5 4 5 2 3 1 4 1 3 4 5 1 3 5 2 1 1 4 1 5 4 4 5 2 2 1 1 2 4 1 1 4 1 1 3 2 1 4 3 3 1 5 5 2 3 1 4 3 5 3 3 2 4 3 4 5 3 3 4 2 5 1 2 1 2 3 5 1 1 1 5 1 1 2 3 3 1 2 4 4 4 3 4 2 3 5 1 4 4 1 4 2 4 3 3 5 1 5 1 3 1 1 2 5 2 4 1 5 3 2 3 5 3 1 5 4 1 5 4 1 5 1 3 2 4 2 1 4 4 1 4 1 2 1 5 5 2 4 2 3 2 5 1 1 2 2 1 5 1 4 2 5 3 2 5 1 1 2 1 1 2 5 5 4 1 3 5 3 1 3 1 1 5 2 2 5 3 5 5 4 2 1 4 1 5 3 2 1 3 5 2 5 4 5 3 3 2 4 5 4 2 4 5 1 4 2 4 1 5 1 2 3 4 5 5 3 4 5 3 2 4 4 3 3 4 2 5 4 4 1 3 5 2 1 2 3 2 2 5 3 5 3 1 4 3 3 3 4 5 1 4 -
Hello Friends, Recently I have attended the interview with a six sigma expert, he give me scenario and told me to find the flaw in it. Below is scenario : When Age is increase and petrol price is also increasing, the tool used is regression. The result shows as strong positive correlation. R=1 What is the flaw? -
Hi, Here is a quick query.... If for a Logistic Regression Test, the Whole Model Test is significant (p<0.05) and the Lack of Fit test is also significant (p<0.05), with just one parameter, what should be our interpretation and next steps. I was using the test to validate one of the Xs. Nirankar
