PLease Respond to the following post with a paragraph, add citations and references.
The problem with this statement is that we are only presented with the “Given” which describes a linear correclation between number of cigarettes smoked and pulse rate. Linear correlation shows a relationship between the two variables – cigarettes and pulse rate- but never shows a causation. To show or prove a causation, a regression analysis needs to be performed.
Correlation is used to indicate relation, while a linear regression is a technique designed both to quantify a positive relationship between random variables, and prove that one variable is dependent on another variable
https://www.investopedia.com/
Brase, C., & Brase, C. (2010). Understanding basic statistics (5th ed.). Belmont, CA: Cengage Learning
Answer preview
determining causation between any two variables might be practically impossible (Hinton, 2014). Establishing the causal relationship between variables, correlations must be performed to indicate the predictive relationship. However, correlation is not typically useful since its presence does not guarantee to portray the existence of the causal relationship. Besides, the mathematical property of probabilistic independence is achieved when the random variables are independent. The most common and useful technique of measuring the degree of correlation is the Person correlation coefficient since is not sensitive to the non-linear relationship between two variables. Therefore, correlations are helpful since they aid to determine a predictive relationship can be practically exploited.
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