All Courses
-
Data Science and Predictive Analytics-HS 650
The Data Science and Predictive Analytics (DSPA) course builds computational abilities, inferential thinking, and practical skills for tackling core data scientific challenges. It explores foundational concepts in data management, processing, statistical computing, and dynamic visualization using modern programming tools and agile web-services. Concepts, ideas, and protocols are illustrated through examples of real observational, simulated and research-derived datasets. Some prior quantitative experience in programming, calculus, statistics, mathematical models, or linear algebra will be necessary. The course uses the statistical computing language R for most demonstrations.
-
CEE 501 066 WN 2017
This course provides an introduction to analysis and forecasting of passenger travel demand. The course objective is for students to understand the fundamentals of discrete choice models, as these are the building blocks for travel demand modeling. By analyzing case studies and participating in a group project, students will also understand how these models are applied in practice for analyzing travel behavior and how it can be expected to change in future scenarios. The range of topics for this course includes an introduction to transportation planning, fundamentals of utility theory and other behavioral theories, binary, multinomial, and nested Logit (discrete choice) models, survey data collection and sampling, scenario analysis, and model forecasting.
-
EDUC 715 001 WN 2017
This class has two goals: a) introducing structural equation modeling as a statistical method as a generalization of Multiple Regression; b) familiarize participants with MPlus as software. MPlus is one of the most widely used programs to run SEM models and is able to run very sophisticated analyses or which we will cover only those that are common in psychological and educational applications (e.g., mediation, moderation, multi-group, multi-level, and missing data handling). The background in statistics of the participants and specific needs will affect pace and coverage of this course. The idea for this course is to acquire practical knowledge in SEM and MPlus, statistical theory (e.g., estimation procedures, identification problems etc.) is not focus of this class but will be discussed as needed.
-
Showcase of Language, Culture and Literature Teaching
This site is an active showcase of successful language learning pedagogical interventions. It is also an archive of examples used in the Canvas Showcase for Language and and Literature Courses in Fall 2016.