Statistics Major
Program Requirements
- Total Units Required: 42
- Ten core courses (30 units)
- At least four elective courses (12 units)
- Grade Requirement: All courses must be passed with a grade of C- or better
Required Courses
| Code | Title | Units |
|---|---|---|
| CSE 1301 | Introduction to Computer Science | 3 |
| MATH 1510 | Calculus I | 3 |
| MATH 1520 | Calculus II | 3 |
| MATH 2130 | Calculus III | 3 |
| MATH 3300 Matrix Algebra or MATH 4301 Linear Algebra | 3 | |
| SDS 3020 | Elementary to Intermediate Statistics and Data Analysis | 3 |
| SDS 4010 | Probability | 3 |
| SDS 4020 | Mathematical Statisitcs | 3 |
| SDS 4130 | Linear Statistical Models | 3 |
| SDS 4310 Bayesian Statistics or SDS 4210 Statistical Computation | 3 | |
| Total Units | 30 | |
Elective Courses
In addition to the required courses, students must complete at least 12 units of electives from the approved list of electives. Typically, this is satisfied by taking 4 courses, worth 3 units each; however, a student may use any number of approved elective courses, as long as the total number of elective units is at least 12.
At least 6 of the elective units must be from SDS courses numbered 4000 or above. At most, 3 units of independent study or research can count towards electives.
In addition to the list below, any SDS course numbered 4000 or above, except SDS 4211, can be counted as an elective.
We will allow undergraduates to take any SDS 5000-level courses that are not listed as undergraduate courses.
Approved Electives
| Code | Title | Units |
|---|---|---|
| CSE 4107 | Machine Learning | 3 |
| CSE 5104 | Data Mining | 3 |
| CSE 5105 | Bayesian Methods in Machine Learning | 3 |
| CSE 5100 | Deep Reinforcement Learning | 3 |
| ECON 4151 | Applied Econometrics | 3 |
| ESE 4030 | Operations Research | 3 |
| ESE 4150 | Optimization | 3 |
| ESE 4170 | Machine Learning and Pattern Classification | 3 |
| ESE 4261 | Statistical Methods for Data Analysis with Applications to Financial Engineering | 3 |
| ESE 4270 | Financial Mathematics | 3 |
| MATH 3010 | Foundations for Higher Mathematics | 3 |
| MATH 4101 | Introduction to Analysis | 3 |
| MATH 4102 | Introduction to Lebesgue Integration | 3 |
| MATH 4501 | Numerical Applied Mathematics | 3 |
| MATH 4502 | Topics in Applied Mathematics | 3 |
| MATH 4560 | Financial Mathematics | 3 |
| SDS 3110 | Biostatistics | 3 |
AP Credit, Waivers, and Course Substitutions
AP credit can be applied for Math 1510 Calculus I, Math 1520 Calculus II.
CSE 1301 Introduction to Computer Science may be waived with approval from the Director of Undergraduate Studies of the Department of Computer Science and Engineering.
Aside from the approved cases listed below, course substitutions will be considered on a case-by-case basis.
- ESE 3260 may be substituted for SDS 3020
- If both MATH 2801 and 2802 are taken, they can be substituted for the entire calculus sequence MATH 1510,1520, and 2130.
Course Transfers
Courses transferred from other accredited colleges and universities can be counted with department approval and with the following caveats:
- Courses transferred from a two-year college (e.g., a community college) cannot be used to satisfy 4000-level requirements.
- Courses from the School of Continuing & Professional Studies cannot be used to fulfill major requirements.
Distinctions in Statistics
Students who satisfy the following requirements may contact the SDS Academic Coordinator to notify the department that they request to graduate with distinctions in their senior year.
Distinction
Complete at least 21 units of SDS courses numbered 4000 or above, excluding independent study courses, achieving at least a 3.7 GPA in these courses. The GPA is weighted by the number of units of each course. If more than 21 units are taken, only the 21 units with the highest grades are used in the GPA calculation.
High Distinction
Complete all requirements for Distinction, and complete an Honors Thesis.
Highest Distinction
Complete all requirements for High Distinction, plus one of the two paths below:
- Graduate Qualifier Path:
- Complete a two-semester graduate qualifier course sequence and pass the graduate qualifier exam for this sequence. Graduate qualifier courses are two-semester course sequences that start in the fall. These qualifier courses can count toward the additional course requirements for Distinction.
- Course Work Path:
- Complete 9 additional units of approved electives, 6 of which must be SDS courses numbered 4000 or above, achieving at least a 3.7 GPA in the 30 units (21+9) required for highest distinction.
Latin Honors
At the time of graduation, the Department of Statistics and Data Science will recommend that a candidate receive Latin Honors (cum laude, magna cum laude, or summa cum laude) if that student has completed the department's requirements for High Distinction or Highest Distinction in Statistics, including an Honors Thesis. The actual award of Latin Honors is managed by the College of Arts & Sciences.
The Honors Thesis
Arts & Sciences majors who want to be candidates for Latin Honors, High Distinction, or Highest Distinction must complete an Honors Thesis. Writing an Honors Thesis involves a considerable amount of independent work, reading, research, writing a paper that meets acceptable professional standards, and making an oral presentation of the results.
Types of Projects
An Honors Thesis can take three forms:
- A thesis that presents significant work by the student on one or more nontrivial statistics or probability problems.
- A project in applied statistics that involves an in-depth analysis of a large data set. To do an honors thesis involving data analysis, it is usually necessary to have completed SDS 3020, SDS 4010, and SDS 4020 (or SDS 3030 and SDS 4030) by the end of the junior year and to have the ability to work with statistical software such as SAS, R, or Python.
- A substantial expository paper that follows independent study on an advanced topic under the guidance of a department faculty member. Such a report would involve the careful presentation of ideas and the synthesis of materials from several sources.
Process and Suggested Timeline
Junior Year, Spring Semester:
- Talk with a faculty advisor about possible projects.
- Complete the Honors Proposal Form and submit it to sdsundergraddirector@wustl.edu.
Senior Year:
- By the end of January, provide the advisor with a draft abstract and outline of the paper.
- By the end of February, submit a rough draft, including an abstract, to the advisor.
- The student and the advisor should agree on a date that the writing will be complete and on a date and time for the oral presentation in mid-March (the deadline is March 31).
Departmental Prizes
Each year, the department considers graduating majors for several departmental prizes and awards a prize to a junior. Recipients are recognized at an annual awards ceremony in April where graduating majors each receive a certificate and a set of honors cords to be worn as part of the academic dress at Commencement. Awards are noted on the student's permanent university record.
Contact Info
| Contact: | Jimin Ding and Joe Guinness |
| Email: | sdsundergraduatedirector@wustl.edu |
| Website: | http://sds.wustl.edu |