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Data Science Minor

Open to Any Major

16-17 Credits

Shippensburg University’s data science minor program focuses on developing the concepts and skills needed to extract meaningful information from data.

Combining computational and statistical thinking, students will be able to effectively use data in many areas:

  • Social sciences (policy impact, census, crime, survey data)
  • Natural sciences (gene sequencing, health records)
  • Humanities (digitized historical records, archeological data)
  • Industry (finance, insurance, manufacturing)

Core courses develop a depth of understanding in coding skills, statistical techniques, and data manipulation and visualization. For the final requirement, students are expected to apply data science concepts to the capstone research experience in their own major.

The minor examines the entire process of data science including the implementation of a practical workflow for analyzing data. Thanks to the increasing prevalence of data in every corner of business, industry, and government, the fastest growing sectors in the mathematical sciences are all related to statistics and data. With applications ranging from financial modeling to government services to consumer marketing, statisticians are key players on a wide variety of multidisciplinary teams in the workplace.

Common careers in this field include:

  • Data scientist
  • Economic analyst
  • Marketing analyst
  • Psychometrician statistician

All of the statistics and data science core courses are taught in a computer classroom to provide hands-on experience with software. Outside the classroom, students are encouraged to attend weekly mathematics department seminars, which touch on areas of research, applications to cognate disciplines, employment opportunities, and more.

Course Work for Data Science Minor

There are no special requirements to enter the Data Science minor, but the first statistics course in the program (MAT 217) is restricted to students with Math Level 5 or above. Course requirements for the minor include an introductory computer programming course, two statistics courses, two data science courses, and a domain-area capstone course chosen from the student’s major program.

Visit the catalog for course descriptions.

Required Courses (16-17 Credits):

Choose one of the following:

  • CMSC 104 - Programming in Python
  • CMSC 110 - Computer Science I
  • ITAN 240 - Python Programming for Business and Analytics
  • SWEN 100 - Intro to Software Engineering
  • ENGR 110 - Modeling and Simulation
  • ENGR 120 - Programming for Engineers 

Choose one of the following:

  • MATH 217 - Statistics I
  • MATH 375 - Probability and Statistics for Engineers

  • MATH 219 - Data Science I
  • MATH 317 - Statistics II
  • MATH 319 - Data Science II 

Discipline-Specific Research Course (2-4 Credits) choose one:

  • BIOL 397 - Introduction to Research 
  • BIOL 398 - Research II
  • COMM 432 - Public Relations Research and Campaigns 
  • CMSC 499 - Senior Research and Development
  • ECON 333 - Research and Analysis in Economics 
  • ENGR 310 - Statistical Process Control 
  • ENGR 311 - Managing Development Processes 
  • EXER 453 - Research Design and Statistics 
  • GEOG 363 - GIS2: Intermediate Geographic Information Systems
  • GEOG 440 - Field Techniques 
  • GEOG 441 - Quantitative Methods 
  • COST 360 - Research Methods in Communication 
  • HIST 386 - History Research Seminar 
  • MATH 326 - Mathematical Modeling 
  • MKTG 430 - Marketing Research 
  • POLI 301 - Political Science Research Methods 
  • PSYC 301 - Experimental Psychology 
  • SCMG 481 - Decision Models for Supply Chain Management
  • SOCI 385 - Elements of Social Research 
  • SOWK 360 - Research Techniques for Social Workers 
  • SOWK 462 - Seminar in Social Work Methods 

Any Majors Interested in a Data Science Minor