STAT 220 Special Topics in Statistics: Methods of Statistical Inference (Spring 2018)
Description: This course builds on material taught in MATH 117, with a focus on confidence intervals and hypothesis testing. Topics include: one- and two-sample methods for proportions and means (including independent and dependent samples), chi-square tests, ANOVA, nonparametric methods, and resampling techniques. Use of SPSS or similar statistical software is required.
Instructor: Chris Casement
Prerequisite: C- or better in MATH 117
Timing: MWF 9:10 – 10:15
STAT 350 Statistical Theory (Spring 2018)
Description: This course is intended for students interested in augmenting their understanding of the topics covered in MATH 117 and Math 227 with a more thorough treatment of the topics. Additional material includes mathematical notation and fundamental concepts used in statistics, basic discrete probability, probability models and distributions, and more in-depth, mathematical treatment of other topics found in MATH 117. The course also develops some basic mathematical (i.e., matrix algebra) and statistical topics needed for analyzing high-dimensional statistical data. Appropriate for students interested in attending graduate school in statistics or related discipline.
Instructor: Yi Lu
Prerequisite: C- or better in MATH 227 or ECON 303 or permission of instructor.
Timing: MWF 1:15 – 2:20
DATA 200 Data Science: Introduction, History, and Case Studies (Spring 2018)
Description: An introduction to data science centered around small projects and case studies. Basic techniques for data acquisition, public data sources, privacy and security, ethical and legal issues. Case studies will include uses of data and data science in industry and public policy and examples of data journalism.
Instructor: Yi Lu
Prerequisite: None
Timing: MWF 10:25 – 11:15
CE 275 – Innovation I (Fall 2017) & II (Spring 2018)
Are you controlling your phone or is your phone controlling you?
Join us in exploring how human societies & individuals are harmed and benefited by technology and take action to avoid technological dangers & optimize benefits to humanity.
The first/second of a two-semester course sequence. In this course, students will engage in creative problem solving applied to implementing a solution to a real-world problem that has social impact. Students will study examples of innovation in historical & contemporary contexts. This course will ask students to act, think and collaborate across disciplines by drawing from the arts, humanities, as well as social and natural sciences in formulating potential solutions. The course will feature opportunities to connect with innovators and entrepreneurs outside of the university setting. Permission of instructors required.
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STAT 120 – Statistical Computing in R (Fall 2017)
This course provides students with an introduction to computing in the popular statistical programming language R. Topics include: data structures, reading and storing data, data transformation and manipulation, accessing and using packages, conditionals, loops, functions, graphics and data visualization, and introductory statistical methods for data analysis. No previous programming experience is required.
