“Correlation does not imply causality” is an important concept when referring to regression. Briefly describe this...

“Correlation does not imply causality” is an important concept when referring to regression. Briefly describe this concept. Provide one example of how it may occur. Not exceed 100 words.

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correlation is used to determine the relationship between two numeric variables. A positive correlation means that the variables are positively dependent on one another that is if one increases(decreases), the other one will increase(decrease) respectively. But correlation does not imply how the vriables are affected by each other. So we can say that "correlation does not imply causation". in the case of regression, though it shows the dependence among variables, it does not imply causation that is what actually caused the variables to behave in such a way.

For example, we can say that the correlation between ice cream sales and homicides is 0.70. This does not imply the causation.Both can be increasing coincidentally. We can use regression and it may imply that homicides is the dependent variable depending on ice cream sales,the data can also support the fact. But actually there is no cause and effect behind this and that is why causation also requires theoretical knowledge and not just numerical evidence. hence we can say that "Correlation does not imply causality" is an imporatnt concept when referring to regression and though it seems like regression provides causation,it actuslly does not.

orchestra answered 1 year ago

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