Relationships in Data Analysis

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Recently, Roger Peng wrote about Relationships in Data Analysis on Simply Statistics. It was a good read and focused on the human side of data analysis. Critical to the success of any analysis project is understanding the nature of the relationships involved. Peng goes on to explore the implications of when roles are combined, and how this can impact the outcome of an analysis. Consider the person sponsoring an analysis also being the audience, how would the communication of this analysis differ is the audience were not the patrons, but were instead deep subject matter experts?

“Often, the quality of an analysis can be driven by the relationships between the analyst and the various people that have a stake in the results. In the worst case scenario, a breakdown in relationships can lead to serious failure.”

While not exhaustive or definitive, I have created an info graphic to categorise some of the combinations that may occur between Patron, Subject Matter Expert, Audience and Analyst. I have given these models a loose name and a possible scenario, but I’m sure others in different domains will find other analogies that work.

I feel the key takeaway here is spending some time upfront to consider the nature of the relationships in each project I work on, so I have some awareness about how to manage these relationships and what risks or implications it might introduce.

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