Statistical and Data Sciences, Minor

FACULTY:
Drew Pasteur, Chair
Marian Frazier, Associate Chair
Qimin Huang
Colby Long
Moses Luri
Jillian Morrison

The Department of Mathematical and Computational Sciences seeks to produce liberally educated Statistical and Data Sciences scholars who will gain skills as they navigate our program and beyond, building strengths in communication, ethics, algorithmic analysis of data, data collection, identification of data quality, manipulation, and application of statistical models for analyzing data in order to identify trends and relationships, make predicitions, and support data-driven decision making and conclusions.

Statistical and Data Sciences, Minor

Consists of six credits:

DATA 10200 - Introduction to Statistics
DATA 10600 - Introduction to Data Science
DATA 20100 - Data Visualization
One of the following courses:
DATA 23100 - Applied Statistical Methods
or
DATA 23000 - Applied Statistics
One of the following courses:
CSCI 10000 - Scientific Computing
or
CSCI 10200 - Multimedia Computing
CSCI 11000 - Imperative Problem Solving

Special Notes

The DATA 10200 requirement may be met by an appropriate statistics course in another campus department, such as BIOL 20300, ECON 11000 , PSYC 25000 , or SOAN 34100 .
Advanced Placement: At most three courses of advanced placement may be counted toward a major, and at most two courses toward a minor. Advanced placement in Statistical and Data Sciences is available to students who have taken an Advanced Placement Examination or an equivalent furnished by the Department of Mathematical and Computational Sciences. Students are urged to take the AP examination for this purpose when possible. Specifically, Wooster credit can be awarded for the AP Statistics, AP Calculus AB, AP Calculus BC, or AP Computer Science A exams. Full detail on the advanced placement policy of the College is explained in the section on Academic Policies.
Only grades of C- or better are acceptable in courses for the major or minor.