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Big Data Analytics - With an Infusion of Statistics for the Modern Student

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2019 ASEE Annual Conference & Exposition


Tampa, Florida

Publication Date

June 15, 2019

Start Date

June 15, 2019

End Date

June 19, 2019

Conference Session

Mathematics Division Technical Session 2

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Rajendran Swamidurai Alabama State University

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Dr. Rajendran Swamidurai is an Associate Professor of Computer Science at Alabama State University. He received his BE in 1992 and ME in 1998 from the University of Madras, and PhD in Computer Science and Software Engineering from Auburn University in 2009. He is an IEEE senior Member.

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Cadavious M. Jones Alabama State University

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Dr. Cadavious M. Jones is an Associate Professor of Mathematics at Alabama State University. He received his BS in 2006 and MS in 2008 from Alabama State University, and PhD in Mathematics from Auburn University in 2014. He is a contributor to the Australian Maths Trust, and member of the MASAMU international research group for mathematics.

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Carl Pettis Alabama State University

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Carl S. Pettis, Ph.D.
Professor of Mathematics
Department of Mathematics and Computer Science
Alabama State University

Administrative role:

Interim Provost
Office of Academic Affairs
Alabama State University

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Uma Kannan Alabama State University

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Dr. Uma Kannan is Assistant Professor of Computer Information Systems in the College of Business Administration at Alabama State University, where she has taught since 2017. She received her Ph.D. degree in Cybersecurity from Auburn University in 2017. She specialized in Cybersecurity, particularly on the prediction and modelling of insidious cyber-attack patterns on host network layers. She also actively involved in core computing courses teaching and project development since 1992 in universities and companies.

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The field of Big data analytics examines large amounts of data to uncover hidden patterns, correlations and other insights. Individuals who have the skill set to effectively and efficiently analyze these large data sets are becoming increasingly valuable to industry and many areas of research. In this paper, we present our three years of experience with structuring, teaching, and assessing a course that actively engages students in real-world data analysis. Our course guides students through methods for data analysis using probabilistic and statistical techniques that are part of the undergraduate curriculum. The process is taught incrementally. We start with techniques that enhance basic principles of statistics and how they relate to data and provide context, then add additional computer based activities using relevant software and coding methods. Thus, students work in an interactive environment in which they are instructed on new techniques and then mentored in the use of those techniques through a series of active learning exercises.

Swamidurai, R., & Jones, C. M., & Pettis, C., & Kannan, U. (2019, June), Big Data Analytics - With an Infusion of Statistics for the Modern Student Paper presented at 2019 ASEE Annual Conference & Exposition , Tampa, Florida. 10.18260/1-2--32155

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