Developing a New Interdisciplinary Computational Analytics Undergraduate Program: A Qualitative-Quantitative-Qualitative Approach

Scotland Leman, Leanna House and Andrew Hoegh

The American Statistician, 2015, vol. 69, issue 4, 397-408

Abstract: Statistics departments play a vital role in educating students on the analysis of data for obtaining information and discovering knowledge. In the last several years, we have witnessed an explosion of data, which was not imaginable in years past. As a result, the methods and techniques used for data analysis have evolved. Beyond this, the technology used for storing, porting, and computing big data has also evolved, and so now must traditionally oriented statistics departments. In this article, we discuss the development of a new computational modeling program that meets these demands, and we detail how to balance the qualitative and quantitative components of modern day data analyses for statistical education.[Received December 2014. Revised August 2015.]

Date: 2015
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DOI: 10.1080/00031305.2015.1090337

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