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Statistics

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Program Snapshot
School
School of Natural Sciences
Department
Mathematics
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Learn to Uncover Valuable Insights from Big Data

The ability to transform vast amounts of data into useful information is a crucial skill in our data-driven world. A minor in Statistics from St. Edward’s prepares you to use statistical methods to analyze real-world data, design experiments, present findings and create solutions to problems in almost any career field.

Why choose a Statistics minor?

With massive volumes of numerical data underpinning the global economy, jobs that require statistics and modeling are growing rapidly. This minor gives you significant experience with statistical theory and practice. It also provides the option to delve into machine learning and advanced computing. You’ll gain knowledge and skills that help prepare you for a broad range of high-tech and in-demand jobs, and to attend graduate school in analytical fields.

What majors does a Statistics minor complement?

A minor in Statistics is a strong choice for students studying the natural sciences, behavioral sciences and business, in which analyzing and leveraging data is vital to problem-solving and successful outcomes. 

For students majoring in Mathematics, a minor in Statistics gives you a specialization within the broader discipline of mathematics that can be applied across numerous areas of interest. Statistical methods are also foundational for many data analysis techniques, making this minor beneficial for students pursuing our Certificate in Data Analysis.

 

 

Explore Details About a Minor in Statistics

Students pursuing a minor in Statistics must complete the following six core courses plus one elective, totaling 24 credit hours.

Required Courses

  • Computing Science Concepts 1 – COSC 2413 (4 hours)
  • Calculus 1 – MATH 2413 (4 hours)
  •  Calculus 2 – MATH 2414 (4 hours)
  •  Introduction to Mathematical Statistics – MATH 3326 (3 hours)
  • Statistical Modeling – MATH 3337 (3 hours)
  • Probability Theory – MATH 3334 (3 hours)

Electives
Choose at least one:

  • Linear Algebra – MATH 3305 (3 hours)
  • Numerical and Scientific Methods – MATH 3338 (3 hours)
  •  Introduction to Data Science – MATH 3339 (3 hours)
  • Special Topics in Statistics – MATH 3335 (3 hours)

For course descriptions, view the current Undergraduate Bulletin (PDF).

Minoring in Statistics gives you a comprehensive understanding of statistical methods. It sharpens your critical thinking, a key skill in data-driven decision-making. The program’s core courses and electives are reinforced through practical applications and projects. You’ll learn to:

  • Identify and apply appropriate statistical models to analyze real-world data, recognizing the assumptions and limitations of each method, and critically evaluating the validity of conclusions drawn from the analysis.
  • Demonstrate proficiency in fundamental mathematical concepts that support statistical reasoning by solving relevant mathematical problems in statistics.
  • Utilize statistical software proficiently to explore, visualize and analyze data, producing clear, data-supported conclusions through hands-on projects and assignments.
  • Communicate statistical findings effectively through written reports, presentations and visualizations, ensuring clarity for both technical and non-technical audiences

The impact of statistical principles on society is far-reaching — from calculating population growth or predicting economic business trends to measuring the effects of environmental pollution or analyzing the effectiveness of a new drug treatment.

Accordingly, the need for professionals with the mathematical and statistical expertise to inspect, analyze, visualize and make conclusions from data is accelerating across industries, including healthcare, engineering, finance, government, marketing and technology. 

Increased demand is seen in the rise of statistician, data scientist and data analyst roles, as well as related careers such as business analyst, biostatistician, quantitative analyst, marketing research analyst and more.

Faculty at St. Edward’s bring a wealth of expertise and industry experience to the classroom. They are passionate about connecting and cultivating lifelong learners, and many are involved with professional organizations and business communities that students can leverage as they pursue internships or full-time employment.

View a list of our faculty members on the Department of Mathematics webpage. Learn about their credentials, and feel free to contact them for more details about the minor in Statistics program.

Suzanne Kennedy
Adjunct Faculty
Email Suzanne Kennedy
Alexis Hailey
Adjunct Faculty
Email Alexis Hailey
Broderick Dickerson
Adjunct Faculty
Email Broderick Dickerson
Lauren Freeman
Visiting Asst Professor of Chemistry
Phone:
Office: North - John Brooks Williams 215
Email Lauren Freeman
David Ledesma
Asst Professor Biological Sciences
Phone:
Office: North - John Brooks Williams 115
Email David Ledesma

Applied Data Science

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Program Snapshot
Program Type
Bachelor of Science
School
School of Natural Sciences
Department
Mathematics
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Become a Data-Driven Decision Maker

The speed and volume of data creation are rapidly escalating, making research and analysis in big data a highly sought-after skill set. Our Applied Data Science program at St. Edward’s prepares you to enter this field with confidence, ready and able to tackle complex problems using data, machine learning and artificial intelligence. 

As a student in this program, you’ll build a strong foundation of analytical skills using computing, statistics, data science and mathematics, while specializing your degree with a minor in a field that suits your interests. Learn how data science can help organizations extract meaningful insights that guide smart decisions and help transform the world for the better. 

The demand for data science is projected to grow by 21% between 2021 and 2031.
U.S. Bureau of Labor Statistics (BLS)

Why earn your Applied Data Science degree at St. Edward’s?

Whether you plan to enter the workforce as a data scientist or analyst in the corporate, nonprofit or government sectors, or pursue a graduate degree, one thing is certain: Your St. Edward’s education will prepare you to succeed. You’ll find opportunities inside and outside of the classroom to learn, give back and achieve your goals. Moreover, your mentors will support you every step of the way.

Build relationships with your professors

You’ll learn in small classes taught by award-winning professors with years of academic and industry experience. They’ll make a point of getting to know you, help you identify and focus on your goals, and provide guidance and insight during and after your college years.

Pair your Applied Data Science major with a minor of your choosing

All Applied Data Science students will choose a minor to pair with their major. This will allow you to build expertise in an additional area to which you can apply your newly acquired skills in data science.

Complete a real-world project related to your minor

Engage in independent and faculty-mentored research in the university’s state-of-the-art Advance Computing Lab. You’ll build a comprehensive Capstone project that you can share with potential employers and graduate schools to showcase your expertise and skills. 

Join a like-minded community of problem-solvers

The St. Edward’s Computer Science and Math clubs bring together students who share a passion for computer science, math and data science. Through meetups, workshops and events, students have fun learning from one another while collaborating on exciting projects that help build their résumés. 

Cultivate professional skills through internships

As an Applied Data Science major, you’ll have access to the funding programs, including paid internships, offered exclusively to STEM students at St. Edward’s by the Institute for Interdisciplinary Science (i4). Leverage the university’s partnerships in the Austin area to network and secure internships.

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Reap the Rewards of Austin

Austin is a hotspot for technology startups, mid-size companies, government agencies, nonprofits and industry giants such as AMD, Google, IBM, Apple, Amazon, Dell, Tesla and Samsung. As an Applied Data Science major, you can explore career paths and practical application of your studies through internships and interactions within the greater Austin community. 

Explore Details About the BS in Applied Data Science

Degree Plan

Major Requirements:
The Bachelor of Science in Applied Data Science requires 54 hours of Applied Data Science major courses, including courses in mathematics, computer science, natural sciences and philosophy. Additionally, students will select any minor (or second major) at St. Edward’s to pair with their Applied Data Science coursework.

General Education Requirements: 
In addition to the major program requirements, all students must satisfy the general education requirements. Talk with your success coach or academic advisor about which courses are right for you.

View and download the full degree plan for the BS in Applied Data Science major (PDF).

Curriculum

  • The BS in Applied Data Science will consist of 15 core courses plus one elective and a minor of the student’s choosing, for a total of 72 to 81 credit hours.
  • Core courses are drawn from the departments of Mathematics, Computer Science, Natural Sciences and Philosophy.
  • Elective courses are drawn from the same departments, and the minor can be any minor that allows at least 9 unique credit hours. Currently this only excludes the Statistics minor.

Innovations in Teaching

  • In Introduction to Data Analysis (MATH 2327), Introduction to Data Science (MATH 3339) and Data Science at Scale (MATH 4340), you’ll apply your skills to team projects with real data and important questions. Build a portfolio of impressive work to show to potential employers.
  • Utilize both R and Python for data analysis, machine learning and statistical modeling across a variety of courses.
  • Complete a Capstone project related to your chosen minor in Data Science at Scale (MATH 4340). Build an end-to-end project that you can share with the world to demonstrate your expertise and skills.

Our Applied Data Science degree ensures you’ll graduate with a strong résumé that showcases your knowledge and skills. 

What You Will Learn

  • Apply appropriate techniques (such as sourcing, cleaning, preparing, analyzing and visualizing) to make decisions using large datasets.
  • Recommend and defend business and scientific decisions based on analysis and modeling of data, and present these decisions to technical and non-technical audiences.
  • Explain the mathematical underpinnings of machine and deep learning models (derivatives, integrals, matrices, probability distributions), as well as their practical usage.
  • Implement computer science techniques such as control structures, object-oriented programming, data structures and algorithms.
  • Demonstrate creating, reading, updating and deleting records in databases, as well as using databases for machine learning models.
  • Students in Data Science at Scale (MATH 4340) will learn how to:
    • Utilize cloud computing to fit and evaluate machine learning models
    • Develop an API to interact with cloud-based models
    • Develop a graphical front-end to interact with cloud-based models

Skills You Will Gain

  • Explore, analyze and visualize data using industry-standard tools and techniques.
  • Create data-driven presentations and convey complex data-driven conclusions to a broad audience.
  • Build and evaluate statistical and machine learning models using both R and Python.
  • Learn core computing concepts, including object-oriented programming, interacting with databases, and programming for the web.
  • Scale models to handle hundreds of millions of rows of data, build pipelines to interact with outside data sources, interact with large language models, and build graphical front-ends for sharing your work.

 

 

As an Applied Data Science graduate, you'll be prepared to take on the role of a data analyst, data scientist or analyst in fields related to your chosen minor. Past data science students have been employed as financial analysts, AI/ML data scientists, data analysts and data scientists. Interested in expanding your expertise by earning a master’s or PhD in data science? This degree puts you on a solid path to pursuing an advanced degree.

Faculty at St. Edward’s bring a wealth of expertise and industry experience to the classroom. They are passionate about connecting and cultivating lifelong learners, and many are involved with professional organizations and business communities that students can leverage as they pursue internships or full-time employment.

View a list of our faculty members on the Department of Mathematics webpage. Learn about their credentials, and feel free to contact them for more details about the Applied Data Science program.

Isabella Mavourneen
Phone:
Email Isabella Mavourneen
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