Statistical Data Science (BS)
The Statistical Data Science major gives students a broad training in the following core areas of data science:
- computer programming and data management
- basic and advanced data analysis
- data visualization
- data ethics
Admission
Students with this major obtain a Bachelor of Science (B.S.) degree. The major can be tailored for a student’s interest in a domain concentration.
In order to apply to the Statistical Data Science major, students must have:
- A GPA of 3.2 or higher in the following classes: MATH 1132Q Calculus II, STAT 1000Q Introduction to Statistics I/STAT 1100Q Elementary Concepts of Statistics, and an introductory programming course (CSE 1010 Introduction to Computing for Engineers, CSE 1729 Introduction to Principles of Programming, or STAT 2255 Statistical Programming).
- completed at least 24 credits, 15 of which must be at the University of Connecticut, with a cumulative GPA of 3.2 or higher.
After entry into the majors, students must maintain a 3.2 cumulative GPA.
Requirements
Students receiving a B.S. in Statistical Data Science are required to take 36 major credits, with one or more courses in each of the core areas, a nine-credit domain concentration sequence, STAT 3255 Introduction to Data Science and STAT 4915 Data Science in Action (capstone)1. To satisfy the information literacy competency and writing in the major requirement, Statistical Data Science majors must also take STAT 4916W Writing in Data Science1.
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Students completing a Biological Data Science domain concentration may take any of the following to meet the capstone and W requirement:
- STAT 4915 Data Science in Action, STAT 4916W Writing in Data Science,
- EEB 4896W Senior Research Thesis in Ecology and Evolutionary Biology, or
- MCB 4897W Senior Research Thesis. Credits in EEB 4896W Senior Research Thesis in Ecology and Evolutionary Biology cannot simultaneously count towards both an Honors thesis in EEB and a Data Science capstone.
Core Area Requirements
| Course | Title | Credits |
|---|---|---|
| Programming and Data Management | ||
| STAT 2255 | Statistical Programming | 3 |
| or ECON 3322 | Open Source Programming with Python for Economists | |
| Basic Data Analysis | ||
| Select one of the following: | 3 | |
| Statistical Methods | ||
| Introduction to Mathematical Statistics I 1 | ||
| Probability | ||
| STAT 3215Q | Applied Linear Regression in Data Science | 3 |
| Data Ethics | ||
| PHIL 3202 | Data Ethics | 3 |
| Data Visualization | ||
| Select at least three credits of the following: | 3-4 | |
| Statistical Computing 1 | ||
| Cartographic Techniques | ||
| Big Data Science for Biologists 2 | ||
| Advanced Analysis | ||
| MATH 2210Q | Applied Linear Algebra | 3 |
| STAT 4255 | Introduction to Statistical Learning | 3 |
| Total Credits | 21-22 | |
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Students completing a Statistics domain concentration must take STAT 3375Q Introduction to Mathematical Statistics I and STAT 3675Q Statistical Computing to meet these requirements.
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Recommended for students completing the Biological Data Science domain concentration.
Domain Concentration Sequence
To complete the domain concentration sequence, students must take at least nine credits from one of the following groups:
Advanced Statistics
| Course | Title | Credits |
|---|---|---|
| STAT 3445 | Introduction to Mathematical Statistics II | 3 |
| Select two of the following: | 6 | |
| Design of Experiments | ||
| Introduction to Biostatistics | ||
| Applied Time Series | ||
| Applied Spatio-Temporal Statistics | ||
| Field Study Internship 1 | ||
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At least and no more than three credits of STAT 4190 Field Study Internship may count towards the major and must be pre-approved by the Department of Statistics for adequate data science content.
American Political Institutions
| Course | Title | Credits |
|---|---|---|
| Select three of the following: | 9 | |
| Making the Modern American Presidency | ||
| Modern American Presidency | ||
| Congressional Apportionment and Redistricting | ||
| Congress in Theory and Practice | ||
| How to Fix an Election: The Politics of Election Administration in the United States | ||
American Political Representation
| Course | Title | Credits |
|---|---|---|
| Select three of the following: | 9 | |
| American Political Parties | ||
| The Art, Science, and Business of Political Campaigns | ||
| Electoral Behavior | ||
| American Political Economy | ||
| Politics of Inequality | ||
| Public Opinion | ||
Biological Data Science
| Course | Title | Credits |
|---|---|---|
| Select three of the following: | 9-12 | |
| Independent Study 1 | ||
| Fundamentals of Ecological Modeling | ||
| Practical Genomics in Ecology and Evolution | ||
| Population Genetics | ||
| Phylogenetics | ||
| Introduction to Molecular Evolution and Bioinformatics | ||
| Practical Methods in Microbial Genomics | ||
| Techniques of Biophysical Chemistry | ||
| Structure and Function of Biological Macromolecules | ||
| Structure and Dynamics of Macromolecular Complexes | ||
| Analysis of Eukaryotic Functional Genomic Data | ||
| Sequence-based Microbial Community Analysis | ||
| Undergraduate Research 1 | ||
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Only three credits of either EEB 3899 Independent Study or MCB 4896 Undergraduate Research can count towards the major, and these credits cannot simultaneously count towards another major or degree.
Students can choose any three courses1 from the list above based on availability, however, interested students might consider choosing subsets of courses from the list above that align with established sub-areas:
| Course | Title | Credits |
|---|---|---|
| Genome Sequencing and Analysis | ||
| EEB 5300 | Practical Genomics in Ecology and Evolution | 3 |
| MCB 3637 | Practical Methods in Microbial Genomics | 3 |
| MCB 5430 | Analysis of Eukaryotic Functional Genomic Data | 3 |
| Phylogenetics and Evolution | ||
| EEB 5348 | Population Genetics | 4 |
| EEB 5349 | Phylogenetics | 4 |
| MCB 3421 | Introduction to Molecular Evolution and Bioinformatics | 3 |
| Ecological Analyses | ||
| EEB 5050 | Fundamentals of Ecological Modeling | 4 |
| EEB 5348 | Population Genetics | 4 |
| MCB 5631 | Sequence-based Microbial Community Analysis | 3 |
| Molecular Structure and Function | ||
| MCB 4008 | Techniques of Biophysical Chemistry | 3 |
| MCB 4009 | Structure and Function of Biological Macromolecules | 3 |
| MCB 4014 | Structure and Dynamics of Macromolecular Complexes | 3 |
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Only three credits of either EEB 3899 Independent Study or MCB 4896 Undergraduate Research can count towards the major, and these credits cannot simultaneously count towards another major or degree.
Financial Analysis
| Course | Title | Credits |
|---|---|---|
| Select three of the following: | 9 | |
| Elementary Economic Forecasting | ||
| Financial Econometrics | ||
| Financial Economics | ||
| Convex Optimization with Python | ||
Marine Science
| Course | Title | Credits |
|---|---|---|
| Select three of the following: | 9-11 | |
| Foundations of Marine Sciences | ||
| Foundations of Marine Sciences | ||
| Marine Biology | ||
| Measurement and Analysis in Coastal Ecosystems | ||
| Experimental Design in Marine Ecology | ||
Population Dynamics
| Course | Title | Credits |
|---|---|---|
| Select three of the following: | 9 | |
| Sociology of Education | ||
| Sociology of the Family | ||
| Sociology of Health | ||
| Sociological Perspectives on Poverty | ||
| Urban Sociology | ||
| Population | ||
Bachelor of Science Requirements
For a Statistical Data Science major that leads to a Bachelor of Science degree, students must take:
| Course | Title | Credits |
|---|---|---|
| Statistics Course | ||
| Select one of the following: | 4 | |
| Introduction to Statistics I | ||
| Elementary Concepts of Statistics (recommended) | ||
| MATH Courses | ||
| Select one of the following MATH sequences: | 8 | |
Sequence 1 | ||
| Calculus I and Calculus II | ||
Sequence 2 | ||
| Advanced Calculus I and Advanced Calculus II | ||
| Select one of the following: | 3-4 | |
| Multivariable Calculus | ||
| Applied Linear Algebra | ||
| Elementary Differential Equations | ||
| Science Sequence | ||
| Select a sequence in one of the following that includes laboratory measurements: 1 | 8-10 | |
Biology | ||
| Principles of Biology I | ||
| Principles of Biology II | ||
or BIOL 1110 | Introduction to Botany | |
Chemistry | ||
Select one of the following sequences: | ||
| Fundamentals of General Chemistry I and Fundamentals of General Chemistry II and Fundamentals of General Chemistry III | ||
| General Chemistry I and General Chemistry II | ||
| Honors General Chemistry I and Honors General Chemistry II | ||
Physics | ||
One of the following sequences: | ||
| General Physics I and General Physics II | ||
| General Physics with Calculus I and General Physics with Calculus II | ||
| Physics for Engineers I and Physics for Engineers II | ||
| Fundamentals of Physics I and Fundamentals of Physics II | ||
| Total Credits | 23-26 | |
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One of these courses may be used to fulfill the CA 3 lab requirement of the University’s general education requirements. In addition, students must take one other CA 3 course from a different subject area, but it need not be a lab course.
University General Education Requirements
Every student must meet a set of core requirements to earn a baccalaureate degree, in addition to those required by the student's major course of study and other requirements set by the student's school or college. For more information about these requirements, please see General Education Requirements.
College of Liberal Arts and Sciences Degree Requirements
Students must meet a set of requirements established by the college in addition to the University's General Education requirements. For more information, see the College of Liberal Arts and Sciences section of this catalog.