Statistics

Chair(s):

Faculty:

Jeff Jonkman
Ryan Miller
Anna Olsen
Chris Olsen
Erik Simpson
Barbara Trish
Jonathan Wells

With the abundance of data being collected in nearly every field of study, the use of statistical methods to acquire useful information from data is becoming an indispensable skill in the humanities as well as the natural and social sciences. The Statistics concentration focuses on the science of learning from data in the presence of uncertainty, and emphasizes statistical approaches and diverse models that are grounded in research questions from multiple disciplines. This concentration emphasizes the application of statistical methods, quantitative reasoning, visualization, computation and communication skills required when working with real-world data from multiple disciplines. Students in the concentration will plan coursework that develops these core skills, irrespective of the individual student’s particular area of application. Thus the concentration serves students who are interested in pursuing graduate degrees or beginning careers in a wide variety of fields.

Students typically start their study of statistics with STA 209 , a course intended for students who have strong quantitative skills. Students who have some previous experience with statistics are encouraged to consult a member of the concentration committee to determine if this course is the most appropriate starting point for them.

Concentration requirements: 24 credits as follows

4. Advanced Courses: 8 credits

CSC 301 - Analysis of Algorithms 4 credits
ECN 329 - Advanced Econometrics 4 credits
ECN 395 - Special Topic as approved the Statistics Concentration Committee*
MAT 316 - Foundations of Analysis 4 credits
MAT 335 - Probability and Statistics I 4 credits or the cross-listed STA 335
MAT 336 - Probability and Statistics II 4 credits or the cross-listed STA 336
MAT/STA 395-Special Topic as approved by the Statistics Concentration Committee*
MAT 444 - Senior Seminar 4 credits *
MAP 499 - A MAP with any Statistics faculty member in the Department of Mathematics and Statistics or a MAP with another faculty member having significant statistical content and approved by the Statistics Concentration Committee.*
STA 309 - Design and Analysis of Experiments 4 credits
STA 330 - Applied Data Science 4 credits or the cross-listed MAT 330
STA 340 - Bayesian Statistics 4 credits

Other Requirements:

At least one course from section 3 or 4 must be taken outside the Mathematics and Statistics Department.
A student may be exempt from taking STA 209 if they are able to demonstrate a strong background in introductory statistical techniques. Exemption from STA 209 will be given by the chair of the Statistics Concentration. A total of 24 credits are still required for the concentration.

Note *

Courses with an * must be approved by the concentration committee.

Statistics Concentration

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