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Correlation

**Correlation **- is a statistical measure to quantify the strength of the relationship between two quantitative and continuous variables. The relationship can be one of the following

Positive - increasing one variable would increase the other

Negative - increasing one variable would decrease the other

No Correlation - increasing one variable has no impact on the other

Correlation is usually denoted by Pearson's Correlation Coefficient (r) and it ranges from -1 to 1.

-1: Perfect negative correlation

0: No correlation

1: Perfect positive correlation

Causation / Causality

**Causation/Causality** is the relationship between an outcome or an event and a potential reason or the cause. Two variables are said to be in a causal relationship when one variable (input variable) leads to or affects the second variable (output variable)

An application-oriented question on the topic along with responses can be seen below. The best answer was provided by

Natwar Lal on 15th June 2019.

Applause for all the respondents- Amlan Dutta, Natwar Lal.

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

Q. 168

Correlation does not prove causation. Assuming continuous data for both, is it safe to say that proven cause effect relationship certainly results in strong correlation between the cause and effect variables? Explain with examples.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.## Share this post

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