Statistics and Data Science

The digital revolution has created vast quantities of data. Extracting knowledge and insight from this avalanche of information is the goal of data science, a rapidly growing field with applications in such areas as marketing, education, and sports, as well as scientific fields such as genomics, neuroscience, and particle physics.

Career Opportunities

Decision-makers have access to more data than ever before, but deriving meaning and actionable insights from that data requires specialized tools and expertise. For that reason, graduates with degrees in statistics and data science are in high demand.

Currently, there is a global data scientist shortage. It is estimated that within the next two years, there will be twice as many data science jobs as there will be people to fill those roles. This means extensive job opportunities for individuals with the necessary education and skills.

Curriculum

UE’s program in statistics and data science combines state-of-the-art tools and techniques from the field of data science with a mathematically rigorous tradition of classical applied statistics. Students in the program will…

  • Engage through project-driven courses. Data analysis projects offered throughout the curriculum expose students to the entire work cycle of predictive modeling, including problem formulation, acquisition and cleaning of data, model selection and fitting, interpretation, and reporting.
  • Master cutting-edge statistical software. Students gain fluency in the statistical software currently in use within business and industry, including R, Python, and BigQuery.
  • Receive a first-class liberal arts education. Working with “big data” requires more than quantitative and technological skills—it also requires an ability to frame questions, to bring diverse teams together, to make ethical and informed decisions, and to communicate results to decision-makers. A UE education provides students with broad foundational knowledge in the arts and sciences, as well as the critical thinking and communication skills that employers value.

Details on program requirements and course descriptions can also be found in the catalog.

Additional Information

  • Sample 4-year Plan Beginning in an Odd Year

    Fall Spring
    Freshman MATH 221 – Calculus I MATH 222 – Calculus II
    STAT 266 – Introductory Statistics with R
    Sophomore CS 210 – Fund. of Programming I
    STAT 267 – Experimental Design
    MATH 365 – Probability
    MATH 341 – Linear Algebra
    Math 466 – Statistics
    CS 215 – Fund. of Programming II
    Junior STAT 361 – Linear Models
    STAT 474 – Techniques for Large Data Sets
    Harlaxton
    Senior MATH 495 – Senior Seminar: Mathematical Modeling STAT 362 – Machine Learning
    STAT 493 – Statistical Modeling

    Note: CS 215* can be replaced by a computer-based course

    Sample 4-year Plan Beginning in an Even Year

    Fall Spring
    Freshman MATH 221 – Calculus I MATH 222 – Calculus II
    STAT 266 – Introductory Statistics with R
    CS 210 – Fund. of Programming I
    Sophomore STAT 267 – Experimental Design
    MATH 365 – Probability
    CS 215 – Fund. of Programming II
    MATH 341 – Linear Algebra
    Math 466 – Statistics
    Junior STAT 361 – Linear Models STAT 362 – Machine Learning
    Senior STAT 474 – Techniques for Large Data Sets
    MATH 495 – Senior Seminar: Mathematical Modeling
    STAT 493 – Statistical Modeling

    Note: CS 215* can be replaced by a computer-based course. Harlaxton: STAT 361 can be taking in the fall of the senior year.

  • STAT Course Frequency Starting In
    STAT 266 - Introductory Statistics with R Annually in Spring Spring 2017
    STAT 267 - Experimental Design Annually in Fall Fall 2017
    STAT 300 - Data Analysis in Real World Annually in Fall Fall 2018
    STAT 361 - Linear Models Annually in Fall Fall 2017
    STAT 362 - Machine Learning Every other Spring Spring 2018
    STAT 474 - Techniques for Large Data Sets Every other Fall Fall 2018
    STAT 493 - Statistical Modeling Annually in Spring Spring 2019
    MATH and CS Course Frequency
    MATH 221, 222 - Calculus Fall, Spring, and Summer
    MATH 365 - Probability Annually in Fall
    Math 466 - Mathematical Statistics Annually in Spring
    MATH 341 - Linear Algebra Annually in Spring
    MATH 495 - Senior Seminar: Mathematical Modeling Annually in Fall
    CS 210, 215 - Introduction to Programming Every Fall and Spring
  • Course Dependancy Chart

Schedule a visit to campus to learn more about this interdisciplinary program.

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Office Phone:
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Office Email:
math@evansville.edu

Office Location:
Room 314, Koch Center for Engineering and Science