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In Data Science and Data Analysis, as in most technical or quantitative fields of inquiry, there is an important distinction between understanding the theoretical underpinnings of the methods and knowing how and when to best apply them to practical situations.

The successful transition from clean pedagogical toy examples to messy situations can be complicated by a misunderstanding of what a useful and insightful solution looks like in a non-academic context.

In this report, we provide examples of data analysis and quantitative methods applied to “real-life” problems. We emphasize qualitative aspects of the projects as well as significant results and conclusions, rather than explain the algorithms or focus on theoretical matters.

Data Science Report Series #3: Data Analysis Case Studies, by Patrick Boily.

Post Author: Patrick Boily

Patrick is interested in the applications of mathematics and statistcs to evidence-based decision support. He has worked on 25+ such projects since 2008. He has extensive experience in data science, machine learning, A.I. and predictive analytics, data cleaning and data visualization.

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