Task forces update campus community on R2 polytechnic designation project
Curriculum
This is an unofficial description for this program. For official information check the Academic Catalog.
Requirements: (18 credits)
18 credits are required, not including the "additional requirements".
Statistics Course (3 credits)
STAT 201 or STAT 216 or STAT 453
9 credits of 300-level STAT and above
STAT 314 Introductory Statistics for Secondary Teachers 3 Credits
STAT 315 Mathematical Statistics I 3 Credits
STAT 401 Biostatistics 4 Credits
STAT 402 Introduction to Categorical Data Analysis 4 Credits
STAT 403 Analysis of Correlated Data 4 Credits
STAT 416 Mathematical Statistics II 4 Credits
STAT 425 Loss and Frequency Distributions and Credibility Theory 4 Credits
STAT 455 Experimental Design 3 Credits
STAT 456 Statistical Computation 3 Credits
STAT 465 Nonparametric Statistics 3 Credits
STAT 476 Topics in Statistics 3 Credits
Electives (6 credits): chosen from the list above, or from DATA courses
DATA 101 Fundamentals of Data Science 3 Credits
DATA 201 Classification Analytics 3 Credits
DATA 202 Estimation & Clustering Anltcs 3 Credits
DATA 203 Advanced Topics in Data Science 3 Credits
DATA 301 Data Science Using Python 4 Credits
DATA 311 Information Visualization 4 Credits
DATA 331 Introduction to Multivariate Analytics 4 Credits
DATA 421 Introduction to Bioinformatics 4 Credits
Total Credit Hours: 18
Note: No more than one course may be used in both the student's major program and the minor in statistics. A minimum GPA of 2.00 in all courses is mandatory, and grades below C– will not be accepted.
Robin Kalder
Professor, Assistant Department Chair
Mathematical Sciences
Viktoria Savatorova
Associate Professor
Mathematical Sciences
Leah Scharfenberger
Associate Professor
Mathematical Sciences
