NSF-Census Research Network - Information Science

INFO7470 - UNDERSTANDING SOCIAL AND ECONOMIC DATA

Vilhuber — Wed, 18 May 2016 20:52:38 +0000

Author(s):

The course is designed to teach students basic and advanced techniques for acquiring and transforming raw information into social and economic data. The 2016 version is particularly aimed at American Ph.D. students who are interested in using public-use and confidential U.S. Census Bureau data, and the confidential data of other American statistical agencies that cooperate with the Census Bureau. We cover the legal, historical, statistical, computing, and social science aspects of the data "production" process. Students will learn some of the statistical procedures necessary to handle the complex linked data sets increasingly available as confidential data, and will apply some of those techniques in class. New ways of accessing restricted access data will be both presented and sometimes tested. Major emphasis is placed on U.S. Census Bureau data that are accessible from the Federal Statistical Research Data Center network, which is adminstered by the Census Bureau on behalf of the collaborating statistical agencies. Graduate students and faculty who are planning to use RDC-based data, or are seriously considering it, should pay particular attention to the lab related to the proposal process. The course will be taught in a mixture of (a) web-based self-paced videos followed by online exercises and in-classroom discussion and additional materials (Sessions 3-8) (b) traditional classroom lectures (Sessions 1-2, 9-14) and labs.

Nodes:

Cornell University

University of Michigan

Duke University / National Institute of Statistical Sciences (NISS)

University of Colorado at Boulder / University of Tennessee

External Link:

Class website

Type:

Graduate Class

Academic year:

Feb-2016 to May-2016

Primary and cross-listed field of class or course:

Number of students:

140

Undergraduate Training - CU - Fall 2012

Vilhuber — Sat, 17 Jan 2015 17:21:02 +0000

Author(s):

Lars Vilhuber

Jeremy Williams

Bill Block

CS 5150 - Software Engineering - is a course given each fall term at Cornell University. The course is "an introduction to the practical problems of specifying, designing, building, testing, and delivering reliable software systems. Other topics covered in lectures include professionalism, project management, and the legal framework for software development. As a central part of the course, student teams carry out projects for real clients. Each project includes all aspects of software development from a feasibility study to final delivery." [*] In the fall of 2012, the Cornell NCRN node submitted a project, which was selected by a number of students. The project contributed to the first user interface for CED²AR.

Nodes:

Cornell University

External Link:

The proposed class project

The current course website

Type:

Undergraduate Research

Academic year:

Sep-2012 to Dec-2012

Primary and cross-listed field of class or course:

Computer Science

Information Science

Number of students:

Undergraduate Training - CU - Summer 2014

Vilhuber — Sat, 17 Jan 2015 17:08:26 +0000

Author(s):

Lars Vilhuber

Undergraduate researchers participated in a scientific replication project (assessing the ability to replicate academic articles in empirical economics journals). The activity was supervised by two graduate students (one of which was NCRN-funded).

Nodes:

Cornell University

External Link:

Description of summer research

Type:

Undergraduate Research

Academic year:

May-2014 to Aug-2014

Primary and cross-listed field of class or course:

Economics

Information Science

Number of students:

Undergraduate training - CU - Summer 2012

Vilhuber — Sat, 17 Jan 2015 17:05:35 +0000

Author(s):

Lars Vilhuber

Students helped us construct facsimiles of confidential datasets that helped guide the development of CED²AR. The activity was supervised by two (non-NCRN) graduate students.

Nodes:

Cornell University

Tags:

CED²AR

Type:

Undergraduate Research

Academic year:

May-2012 to Aug-2012

Primary and cross-listed field of class or course:

Economics

Information Science

Number of students:

36-315 Statistical Graphics and Data Visualization

Shelly Hall — Wed, 14 Jan 2015 00:11:19 +0000

Author(s):

Stephen Fienburg and William Eddy

Statistical Graphics & Visualization is a 300-level elective class for sophomores, juniors, and seniors in Statistics, Information Systems, Computer Science, Math, and other majors interested in visualizing data. This course also satisfies the Creating General Education requirement for Dietrich College and is highly oversubscribed with a long waitlist every year.

Students learn how to extract, summarize, and visualize structure and features for low- and high-dimensional data. The class is taught in R, but other languages could be subsituted. For the final project, teams of students develop hypotheses and create statistics graphics to look for supporting or contradictory evidence. Projects are presented in poster or website form.

Nodes:

Carnegie-Mellon University

External Link:

Course link at CMU

Type:

Undergraduate Class

Academic year:

Sep-2012 to May-2013

Primary and cross-listed field of class or course:

Number of students:

INFO 7470 - Understanding Social and Economic Data

Shelly Hall — Tue, 13 Jan 2015 17:39:11 +0000

Author(s):

Vilhuber, Lars

Abowd, John M.

The course is designed to teach students basic and advanced techniques for acquiring and transforming raw information into social and economic data. The 2013 version is particularly aimed at American Ph.D. students who are interested in using confidential U.S. Census Bureau data, and the confidential data of other American statistical agencies that cooperate with the Census Bureau. We cover the legal, statistical, computing, and social science aspects of the data "production" process. Major emphasis is placed on U.S. Census Bureau data that are accessible from the Bureau's Research Data Center network. Graduate students and faculty who are planning to use RDC-based data, or are seriously considering it, should pay particular attention to the labs related to the proposal process. The course, created and managed by Cornell University, had participants from 11 sites nationwide, including several nodes and other universities that had recently opened or were considering opening Research Data Centers.

Nodes:

Cornell University

University of Michigan

Duke University / National Institute of Statistical Sciences (NISS)

University of Colorado at Boulder / University of Tennessee

Tags:

History

Census Bureau

Federal Statistical System

Research Data Center

External Link:

Class website