I received an email from a reader after my last blog on interrupted time series asking for additional references on ITS techniques. The Experimental and Quasi-Experimental Designs for Generalized Causal Inference book noted in that article is excellent, as is the timeless Campbell and Stanley classic, Experimental and Quasi-Experimental Designs for Research, a staple of university social science methodology courses for generations.

Indeed there is much in common between social science methods and BI supporting the “science of business”. Both endeavors strive to “prove” the cause and effect of planned interventions using randomized experiments that, subject to probability limitations, can reasonably ensure that differences in treated and untreated groups are the result of the intervention and not confounding outside variables. Unfortunately, business, like the social sciences, is often not the ideal environment for true experimental methods, and in many cases must rely on less intrusive non-randomized or quasi-experimental designs. Humans and business are, alas, not crops and soil.

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