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This analysis excludes vital input variables that are familiar

to horizontal shale players. Inclusion of those inputs should

significantly increase the Correlation Coefficient in this example. 

Multiple Regression is a very useful way to gauge the impact of an aggregate of multiple input variables on a desired outcome.  Multiple Regression is also an excellent way to see which input variables exercise the greatest impact on the desired output (EUR in the above simplistic example).  In turn, the ranking of inputs provides a pathway to tweaking the most inportant inputs for improved results.  Also, a poor Correlation Coefficient (R-squared) suggests that there are important input variables that have not been considered.

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