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 |
Office Phone
812-488-1234
Office Email
math@evansville.edu
Office Location
Room 314, Koch Center for Engineering and Science
