Hi,

Read please the following review paper. Hope this helps. This is just for start. Then, you can go forward using many other sources.

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC374386/

Yours,

Hamid

Correlation will simply tell you the relation between two variables on the other hand regression helps to understand the degree of realtion two variables i.e., weak or strong relation.

First of all, linear correlation can be calculated between two only variables, and is a symmetrical relationship. In linelar regression you have one or more independent variables and a dependent variable, the variability of the latter being explained by the independent in an asymmetrical way. If you have only two variables (i.e. only one independent) R^2 is equal to the squared r (r^2)

Correlation measures the strength and direction of a linear relationship between two variables, while regression goes a step further by modeling and predicting the impact of one or more independent variables on a dependent variable. Correlation does not imply causation, merely showing association, whereas regression can provide insights into potential cause-and-effect relationships.