Real Analysts Make Groups

Managers love lists. Readers devour lists. Buzzfeed’s business model rests on lists. Lists, though, remain a dumb approach to organize anything. A better way exists.

Lists or, specifically, rankings suffer from three flaws. One, items included in the list lack distance. The manager or the audience cannot determine how proximal or distal (fancy words for similar or dissimilar) items on a list appear. Two, listed items are often arbitrary to the point of uselessness. The order of listing Harvard, Yale, and Stanford matters little as all three higher education institutes would be considered elite by any measure. Three, methods to achieve lists can be dubious, hidden, or both. Fortunately, a different, better method can be found.

Groups provide a superior approach to lists because it can resolve the three flaws associated with lists. One, groups are formed based on distance. Items within the group are proximal (again, fancy word for similar) while groups are distal (yes, fancy word for dissimilar). Two, Harvard, Yale, and Stanford would form a group while Hamline, Fontbonne, and Lake Forest would form a different group. A set of attributes or characteristics serve to include some items and exclude other items. Three, methods to form groups can be obvious, transparent, or both. For these reasons, group served as a better method compared to lists.

For the analyst, several tools or methods are available to form groups, including: analysis of variance (ANOVA), analysis of covariance (ANCOVA), correlation, regression, factor analysis, cluster analysis, and multidimensional scaling. Throughout this blog, I will go through these tools including how to conduct them in Excel. 

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