Introduction to Multilevel Modeling (Online Workshop)
Limited to 25 participants
Workshop Description
Course Proposal Support
The ISSR s
Communication - Sample Plan - 18 Credit Hours
Required Course - SOC 508, STP 533, POS 604 - Choose One
Electives:
COM 608 - Mutivariate Stat Analysis Data Comm
MGT 791 - Seminar: Qualitative Research
EDP 502 - Introduction to Data Analysis
COM 691 - Seminar: Applied Experimental Design
GCU 593 - Applied Project
Criminal Justice - Sample Plan - 18 Credit Hours
Required Course - SOC 508, STP 533, POS 604 - Choose One
A Socio-legal Biography of Nanotechnologies, 1994-2014
Michael Bennett, School for the Future of Innovation in Society
Engaging College Students in Analyzing Human Papillomavirus (HPV) Vaccine Messages on YouTube and Developing Public Health Education
Angela Chen, College of Nursing and Health Innovation
Inclusive Innovation in the Age of Big Data and the Internet of Things
Pauline Cheong, The Hugh Downs School of Human Communication
Video can capture a subtle, multi-layered record of situations and environments we observe and study. It captures not only what is said but how it is said, actions and reactions, the appearance of the environment and individuals and how they interact, and so much more. This workshop will focus on techniques for analyzing video and audio data in all of its nuance and richness.
Best Practices for allocation of prize money for collaborative research posters with multiple student authors.
All ISSR prize money should be allocated to students, not faculty or staff.
On posters in which the study design, data collection, data analysis, and poster preparation was completed by a student first-author, ISSR recommends that the bulk of the prize money should go to the first-author student.
Please bring your laptops for this hands-on, full day workshop on Social Network Analysis.
Uncertainty in outcomes can orginate from multiple sources such as measurement errors in data collection, model identification, parameter uncertainty, and process stochasticity. In this workshop we will primarily focus on the last two types of uncertainties, since the data used in the model are from multiple sources and are used as fixed point estimates for parameters. The predictions of a model are highly dependent on the quality of the data used for parameterization. Hence, it is critical that care be given to the precision of the data available and that uncertainty in m