This information is for undergraduate students planning to add either the "Statistics" major or the "Statistics & Computer Science" major by:

• Transferring or changing majors
• Double- or Triple-Major
• Dual Degree

The Department of Statistics has certain entry requirements that must be completed before joining the program.

For more information about transferring into the Stat&CS major, please see our transfer guide here.

If you’re already in LAS: The Curriculum Change form is available online. LAS students may now submit their requests to change from one LAS major to another LAS major using the college’s Curriculum Change Form.

All Curriculum Change requests will undergo a final review by a dean/advisor in the College of LAS. Students will receive email notifications when 1) their request has been submitted and 2) their request is approved, pending, or denied. The entire process should take several business days as with our other online forms.

If you’re in DGS or another college: You must go through the Intercollegiate Transfer (ICT) process to move into LAS and Statistics. Details about ICT can be found here.

How to Officially Add Statistics as a Second Major

If you’re already in LAS: You will need to contact the Admissions & Records Officers in the College of LAS to request a multiple major form. Details about adding a second major can be found here.

If you’re currently in another college: You will need to apply for a second degree in LAS. Details about the dual degree process can be found here.

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Statistics Major Degree
The major, administered by the Department of Statistics, is designed to provide students with an understanding of the concepts of statistical inference and a familiarity with the methods of applied statistical analysis. A major in statistics will prepare students for a career in business, industry, or government, and for further graduate study in statistics or in a related area.

The following courses are required in the Statistics major:

Calculus sequence:

• MATH 220/MATH 221 -  Calculus I
• MATH 231 -  Calculus II
• MATH 241 - Calculus III

Mathematical Statistics sequence:

• STAT 107 - Data Science Discovery OR STAT 200 - Statistical Analysis OR STAT 212 - Biostatistics
• STAT 400 - Statistics and Probability I
• STAT 410 - Statistics and Probability II

Statistical Modeling sequence:

• MATH 257 - Linear Algebra with Computational Applications OR MATH 415: Applied Linear Algebra
• STAT 425 - Statistical Modeling I
• STAT 426 - Statistical Modeling II*

Choose four of the following advanced electives in Statistics:

• STAT 385 - Statistical Programming Methods
• STAT 424 - Analysis of Variance
• STAT 427 - Statistical Consulting
• STAT 428 - Statistical Computing
• STAT 429 - Time Series Analysis
• STAT 430 - Topics in Applied Statistics
• STAT 431 - Applied Bayesian Analysis
• STAT 432 - Basics of Statistical Learning
• STAT 433 - Stochastic Processes
• STAT 434 - Survival Analysis
• STAT 440 - Statistical Data Management
• STAT 443 - Professional Statistics
• STAT 447 - Data Science Programming Methods
• STAT 448 - Advanced Data Analysis
• STAT 480 - Big Data Analytics
• MATH 444 - Elementary Real Analysis OR MATH 447 - Real Variables

*Students who entered the Statistics major before Fall 2021 may take STAT 420 instead of STAT 426.

Credit hours in major:  42 - 45 credit hours

Students must also complete the College of LAS general education requirements: https://las.illinois.edu/academics/requirements/gened

Students in the College of LAS need a minimum of 120 total credit hours to graduate.

Click here for a sample course plan and major planning worksheet.

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Statistics and Computer Science Major Degree

This major provides students with a strong foundation in both the study of Statistics and the field of Computer Science, with opportunities for advanced exploration in both areas. Students gain a fundamental understanding of and rigorous training in statistical analysis, probability, mathematics, computing, and computer science. 

The following courses are required in the Statistics & Computer Science major:

Mathematical Foundation:

• MATH 220/MATH 221 -  Calculus I
• MATH 231 -  Calculus II
• MATH 241 - Calculus III
• MATH 257 - Linear Algebra with Computational Applications OR MATH 415: Applied Linear Algebra

Computer Science Foundation:

• CS 124 – Introduction to Computer Science I
• CS 128 – Introduction to Computer Science II
• CS 173 – Discrete Structures
• CS 222 – Software Design Lab
• CS 225 – Data Structures
• Choose one of the following combinations:
  • CS 233  - Computer Architecture AND CS 241 – System Programming
    OR
  • CS 240 – Introduction to Computer Systems AND two CS courses at the 400 level above CS 403, excluding CS 421 and CS 491. These two courses must be distinct from all other courses used to fulfill program requirements or options.
• CS 357 – Numerical Methods I
• CS 374 – Introduction to Algorithms & Models of Computation
• CS 421 – Programming Languages & Compilers

Statistics and Probability Foundation:

• STAT 107 - Data Science Discovery OR STAT 200 - Statistical Analysis OR STAT 221 - Biostatistics
• STAT 400 - Statistics and Probability I
• STAT 410 - Statistics and Probability II
• STAT 425 - Statistical Modeling I
• STAT 426 - Statistical Modeling II

Statistical Application Electives – Choose one of the following:

• STAT 428 – Statistical Computing
• STAT 431 – Applied Bayesian Analysis
• STAT 432 – Basics of Statistical Learning
• STAT 434 – Survival Analysis
• STAT 448 – Advanced Data Analysis

Computational Application Electives – Choose one of the following:

• CS 410 – Text Information Systems
• CS 411 – Database Systems
• CS 412 – Introduction to Data Mining
• CS 446 – Machine Learning
• CS 481 – Advanced Topics in Stochastic Processes & Applications
• CS 482 - Simulation

Credit hours in major:  68 - 72 credit hours

Students must also complete the College of LAS general education requirements: https://las.illinois.edu/academics/requirements/gened

Students in the College of LAS need a minimum of 120 total credit hours to graduate.

Click here for a sample course plan and major planning worksheet.

Students who entered the Stat&CS major before Fall 2021: please click here for degree requirements and sample course plan.

For more information about transferring into the Stat&CS major, please see our transfer guide here.

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As of the Spring 2022 semester, requirements for the Statistics minor have changed, and students are no longer required to select a track for completion. Going forward, all students designating a Stat minor will follow the below requirements. Students enrolled in a previous version of the Stat minor may still be following the applied or mathematical track of the minor and can click here to see their requirements. Requirements and minor progress can also be found by running a DARS audit.

Prerequisites

To complete all required courses in the Stat minor, students will need to take calculus through MATH 241; although some of the 100-200 level courses will require only MATH 220/221 or MATH 231 for completion. Prerequisites for all minor required courses should be followed as written in the Course Explorer.

Registration

Due to the continued growth and high demand of Statistics courses, many of course offerings hold major restrictions to ensure the highest priority to our majors. Pursuing a Stat minor does not grant a student priority registration rights for major restricted courses. Additional information on our course restrictions and when they will be removed can be found here.

Required Courses (17-22 hrs) 

At least three courses must be in Statistics.

* denotes preferred courses

1. Statistical Concepts

Select one of the following:

STAT 100: Statistics*

STAT 107: Data Science Discovery*

ACE 261: Applied Statistical Methods

CPSC 241: Intro to Applied Statistics

ECON 202: Economic Statistics I

EPSY 280: Elements of Statistics

PSYC 235: Intro to Statistics

SOC 280: Intro to Social Statistics

2. Data Analysis

Select one of the following:

STAT 200: Statistical Analysis*

STAT 207: Data Science Exploration*

STAT 212: Biostatistics

ECON 203: Economic Statistics II

3. Linear Algebra

Select one of the following:

MATH 225: Introductory Matrix Theory

MATH 257: Linear Algebra with Computational Applications*

MATH 415: Applied Linear Algebra

--MATH 416 or ASRM 406 can be substituted for applicable students

4. Mathematical Statistics

Select one of the following:

STAT 400: Statistics & Probability I*

ASRM 401/STAT 408: Actuarial Statistics I

MATH 461: Probability Theory

5. Advanced Statistical Methods

Select two of the following:

STAT 385: Statistics Programming Methods

STAT 410: Statistics and Probability II (if STAT 400 is completed) 

   or ASRM 402/STAT 409: Actuarial Statistics II (if ASRM 401/STAT 408 or MATH 461 is completed)            

STAT 420: Methods of Applied Statistics*

    or STAT 425: Statistical Modeling I       

STAT 424: Analysis of Variance

STAT 426: Statistical Modeling II (If STAT 425 is completed)

STAT 428: Statistical Computing

STAT 429: Time Series Analysis

STAT 430: Topics in Applied Statistics

STAT 431: Applied Bayesian Analysis

STAT 432: Basics of Statistical Learning

STAT 433: Stochastic Processes

STAT 434: Survival Analysis

STAT 440: Statistical Data Management

STAT 443: Professional Statistics

STAT 447: Data Science Programming Methods

STAT 448: Advanced Data Analysis           

STAT 480: Big Data Analytics

ECON 471: Intro to Applied Econometrics

--STAT 430 may be repeated for fulfillment of the Advanced Statistical Methods requirement if the topics differ.

--Courses with a statistical focus at the 300- or 400-level offered by other departments may be accepted as satisfactory for this requirement pending a review of a current syllabus supplied to the Statistics Advising office. Students are encouraged to contact stat-undergrad@illinois.edu with questions and to submit syllabi of potential courses.

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The Certificate in Data Science option allows undergraduate students to receive recognition for completing coursework that provides an understanding of the discipline of data science including exposure to data structures and data sources, statistical principles, computing and analytics, data management, and data science applications. Courses on the Approved List under Interdisciplinary Data Science include subject matter courses and courses that require substantial interpretation of data and report writing. Students completing the Certificate will be presented with an official certificate document and will be free to use this credential on a CV, resume or application for advanced study.

Data Science Course Requirements

For completion of the Certificate in Data Science, students must complete at least four courses (3-4 credit hours each) for a total of 12-16 credit hours of coursework from the Approved List of Data Science Courses below. Two 3-4 credit hour courses are required from Group 1 on the Approved List below. One 3-4 credit hour course is required from each of Groups 2 and 3 on the Approved List.

All courses applied to the certificate may also be counted toward the requirements of the student's declared major. Students are not guaranteed a seat in a course required by the certificate, but are welcome to enroll in courses where seats remain available after any restriction that may have been placed has been removed. No course substitutions will be approved.

Requirements for the Data Science Certificate were updated in January 2023. Students who began the Certificate before Fall 2022 may use this previous version.

Requesting the Certificate

The certificate is sent in PDF format to those who have filled out this request form after completing all requirements. These are usually sent in January (for requirements completed in fall) or June (for requirements completed in spring).

Approved List of Data Science Courses:

1. Introduction to Data Science

• STAT 107: Data Science Discovery, 4 hours

(Equivalent to CS 107 and IS 107)

2. Intermediate Data Science

• STAT 207: Data Science Exploration, 4 hours

3. Linear Algebra (Choose 1 course*)

• MATH 227: Linear Algebra for Data Science, 3 hours
• MATH 257: Linear Algebra with Computational Applications, 3 hours

4. Interdisciplinary data science (Choose 1 course*)

• STAT 385: Statistical Programming Methods
• STAT 420: Methods of Applied Statistics
• STAT 428: Statistical Computing
• STAT 430: Topics in Applied Statistics (must be a DS-focused section as approved by Stat Dept)
• STAT 432: Basics of Statistical Learning
• STAT 440: Statistical Data Management
• STAT 447: Data Science Programming Methods
• STAT 448: Advanced Data Analysis
• STAT 480: Data Science Foundations
• CS 225: Data Structures
• CS 277: Algorithms and Data Structures for Data Science
• CS 307: Modeling and Learning in Data Science
• ECON 471: Intro to Applied Econometrics
• GEOG 371: Spatial Analysis
• GEOG 379: Intro to GIS Systems
• IS 467: Ethics and Policy for Data Science
• IS 477: Data Management, Curation & Reproducibility
• LING 402: Tools & Tech Spch & Lang Proc
• LING 406: Intro to Computational Ling
• MCB 432: Computing in Molecular Biology
• PS 230: Intro to Pol Research
• SOC 380: Social Research Methods
• SOC 488: Demographic Methods

* Students who have completed MATH 415, MATH 416, or ASRM 406 do not have to complete MATH 257 as a second linear algebra course. However, those students must complete a second Interdisciplinary Data Science elective from Group 4 to satisfy Certificate requirements.

The Computational Science and Engineering certificate program is designed to provide STAT undergraduate students an opportunity to develop a solid base in problem solving using computation as a major tool for modeling complicated problems in science and engineering. This CSE Certificate option is not an academic major or minor, but an additional credential only available to students currently enrolled in the Statistics undergraduate degree program at the University of Illinois Urbana-Champaign.

The program is designed so that students can fit it within the required courses in the student’s home department, without the need of taking any additional hours that are distinct from already required coursework. To receive a certificate in “Computational Science and Engineering”, students must complete the required courses listed below. The Application courses are strongly recommended to be in the student’s primary field of study. The minimum coursework required is 12 hours and this fulfills the prerequisite for a CSE certification. 

How to Add CSE Certificate:
Students currently enrolled in Statistics can register for the CSE undergraduate Certification Option by completing the CSE Registration Form before the completion of the course requirements.

Course Requirements:

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Receiving Certificate
Once you have completed the certification requirement, the student must submit a CSE Approval Form (must log in with university credentials). You are not eligible to elect this concentration if you have completed all the required coursework before you enroll in the concentration. Concentrations are not awarded retroactively. Certificates are issued three times per year: during the first weeks of December, May, and August.

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LAS Honors Program
The mission of the James Scholar Program within the College of Liberal Arts & Sciences is to empower our students to be global citizens and global stewards; to enlighten them with deeper understanding of the diverse world in which they live; and to engage with the core values and responsibilities of moving toward a sustainable future.

There are two methods of entry into the James Scholar Program: invitation and self-nomination. The instructions vary depending on whether you’re an incoming freshman, transfer student, a current student at U of I, or an intercollegiate transfer student.

Learn More

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