Interpreting Regression Analysis Results


While regression analysis serves as a powerful tool in addressing a wide variety of business issues, it is critical to understand the limits of regression analysis in order to interpret findings most accurately. One of the most common misunderstandings in regression analysis is the assumption that a strong relationship between a dependent variable and an explanatory variable means that the explanatory variable causes changes in the dependent variable. However, this is not always true. It is possible that the reverse is true; that the dependent variable causes changes in the explanatory variable. Linear regression calculations pay no attention to the direction of the relationship.

Another common occurrence is the relationship of unforeseen variables to what is being analyzed. It is possible that the explanatory variable is not a factor in the determination of the dependent variable. For example, one might think that, in a manufacturing environment, an increase in inventory levels will result in a direct increase in labor costs, perhaps based on the assumption that higher inventory levels require additional labor to manage. However, it is important to understand that an increase in overall production can have a direct and simultaneous causal effect on both inventory levels and labor costs. Achieving higher production levels requires additional production capacity (labor) and results in a higher level of inventory as goods await distribution.




Translating Strategy into Shareholder Value. A Company-Wide Approach to Value Creation
Translating Strategy into Shareholder Value: A Company-Wide Approach to Value Creation
ISBN: 0814405649
EAN: 2147483647
Year: 2003
Pages: 117

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