Analytics
Professor Jeff Bay, Chair, Division of Mathematics and Computer Science
Assistant Professor Anna Engelsone, Coordinator
Analytics is an interdisciplinary field combining mathematics, computer science and statistics that integrates knowledge needed to draw insights from data. A minor in Analytics is a valuable complement to majors in the biological and behavioral sciences where sophisticated methods of data analysis are increasingly common and researchers with this expertise are in high demand. It is also a valuable addition to students majoring in a business-oriented field (see also the major in Business Analytics), as businesses increasingly make use of data analysis, forecasting and optimization techniques to drive efficiency and profit. Students in other majors wishing to supplement and enhance their liberal arts education will find these skills to be broadly applicable and exceptionally marketable.
Students successfully completing this program of study will have achieved the following learning outcomes:
- Communicate mathematical ideas with precision and clarity in both written and oral form to a variety of audiences.
- Understand the logic behind statistical inference – the science of drawing conclusions from limited data – and be able to assess the role of variability in estimations.
- Confidently use software to store, organize, manipulate and analyze large quantities of data.
Students choosing the first option of courses (MTH 321/CSC 314) will deepen their understanding of statistical science and learn more advanced data-manipulation techniques whereas those choosing the second option of courses (MTH 305/MTH 3xx) will learn to use mathematics to model and optimize real-life phenomena.