This PPT slide, part of the 155-slide Strategic Analysis Primer PowerPoint presentation, presents a series of critical questions to consider prior to conducting a regression analysis. It emphasizes the importance of clarity regarding the predictive and dependent variables. Identifying which variable serves as the predictor can sometimes be straightforward,, but it often requires careful consideration of causation. This highlights the need for a thoughtful approach to ensure accurate modeling.

The slide further prompts the analyst to evaluate the explanatory variables that should be included in the regression. It warns against spurious correlations, urging analysts to think independently about logical factors that should be considered. Additionally, it advises against including explanatory variables that are highly correlated with one another, which could distort the results and lead to misleading conclusions.

Another key point raised is whether the regression should include an intercept term. This involves assessing the extent to which the data can be reasonably extrapolated and whether the regression line should intersect the origin. The implications of a zero value for an explanatory variable on the predictive variable are also questioned, indicating a deeper level of analysis is necessary.

Lastly, the slide addresses the importance of having a sufficient number of observations. It suggests a rough rule of thumb, recommending at least ten observations for each explanatory variable. This underscores the necessity of robust data to support reliable outcomes in regression analysis. Overall, the slide serves as a foundational guide for analysts to ensure they are adequately prepared before embarking on regression modeling.

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