'Big Data' Data Sets for Undergraduate Applied Statistics Courses

• Activity Number: 387
• Type: Roundtables
• Date/Time: Tuesday, August 6, 2013 : 12:30 PM to 1:50 PM
• Sponsor: Section on Statistical Education
• Author(s): John McKenzie*+
• Companies: Babson College
• Keywords: Analytics ; Data Deluge ; Immense ; Massive ; Three Vs

Abstract

In 2005, Roger Magoulas introduced the term "Big Data" to denote data sets that are impossible to manage and analyze using traditional tools due to their size and complexity. An excellent way to explain such data is a modified form of Doug Laney's Three Vs. The first V, volume, refers to the massive amounts of data generated by today's technology. The second V, variety, has two components. First, most of these data sets are not spreadsheets of numerical values. Second, these data sets come from a wide range of sources (astronomical transmission, financial transactions, genetic sequences, online searches, social networking activities, etc.). The third V, velocity, brings up the rate of change in these data. Introducing such data into the undergraduate statistics curriculum should be done to prepare students for their future. This roundtable session will discuss examples of Big Data data sets that have one or more of the four characteristics of such data described above. We also will converse about what has worked and what hasn't worked when introducing Big Data into the curriculum.