Abstract Details
Activity Number:
|
480
|
Type:
|
Invited
|
Date/Time:
|
Wednesday, August 6, 2014 : 10:30 AM to 12:20 PM
|
Sponsor:
|
Section on Statistical Education
|
Abstract #310932
|
View Presentation
|
Title:
|
Teaching Concepts in Computing with Data
|
Author(s):
|
Deborah Nolan*+ and Duncan Temple Lang
|
Companies:
|
University of California, Berkeley and University of California
|
Keywords:
|
statistical computing ;
undergraduate education
|
Abstract:
|
Whether they enter the workforce with a bachelor's degree or a PhD in statistics, the new generation of statisticians will encounter an ever-changing array of technologies, data formats, and programming languages and paradigms. Successful statisticians will need skills to, e.g., access and integrate large amounts of data, manipulate complex data into forms more conducive to statistical analysis, and produce interesting presentations of data. The importance of these innovations on the access, analysis, and visualization of data makes a strong case for broadening the undergraduate statistics curriculum to include these non-traditional topics. We will discuss an ongoing effort at our institution to have students engage in creative, complex data projects that are not typically encountered in traditional computing and methodology classes. The aim is to provide students with a deeper, richer appreciation for the practice of statistics. Additionally, we have found that this approach adds a new dimension to the statistics curriculum because it exposes students to modern methodologies not typically encountered in the undergraduate curriculum.
|
Authors who are presenting talks have a * after their name.
Back to the full JSM 2014 program
|
2014 JSM Online Program Home
For information, contact jsm@amstat.org or phone (888) 231-3473.
If you have questions about the Professional Development program, please contact the Education Department.
The views expressed here are those of the individual authors and not necessarily those of the JSM sponsors, their officers, or their staff.
Copyright © American Statistical Association.