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**Residual **is the difference between the observed value and the predicted value. Observed value is the actual data point while predicted value is the value obtained from the regression equation. On a residual plot, it is the vertical difference between the observed point and the line

**Residual Analysis** is the study of residual plots to validate the goodness of a regression model. For a good model, the residuals have to be random and normally distributed

An application-oriented question on the topic along with responses can be seen below. The best answer was provided by Senthilkumar G on 19th Jun 2020

Applause for all the respondents - Raj Saxena, Rajeshwari, Senthilkumar G, Tushar Maradwar

Also review the answer provided by Mr Venugopal R, Benchmark Six Sigma's in-house expert.

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## Share this post

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