Bachelor of Arts (BA) Degree with a Major in Statistics
Program Learning Outcomes for the BA Degree with a Major in Statistics
Upon completing the BA degree with a major in Statistics, students will be able to:
- Apply fundamental theory in probability and statistical inference.
- Apply and evaluate statistical models.
- Apply statistical computing for data analysis and data science.
- Demonstrate competency as a professional statistician.
- Effectively communicate as a professional statistician.
Requirements for the BA Degree with a Major in Statistics
For general university requirements, see Graduation Requirements. Students pursuing the BA degree with a major in Statistics must complete:
- A minimum of 16 courses (49-56 credit hours, depending on course selection) to satisfy major requirements.
- A minimum of 120 credit hours to satisfy degree requirements.
- A minimum of 11 courses (34 credit hours) taken at the 300-level or above.
- A maximum of 3 courses (9 credit hours) in departmental (STAT) coursework from study abroad or transfer credit. For additional departmental guidelines regarding transfer credit, see the Policies tab.
The courses listed below satisfy the requirements for this major. In certain instances, courses not on this official list may be substituted upon approval of the major’s academic advisor or, where applicable, the department's Director of Undergraduate Studies. (Course substitutions must be formally applied and entered into Degree Works by the major's Official Certifier.) Students and their academic advisors should identify and clearly document the courses to be taken.
Summary
Code | Title | Credit Hours |
---|---|---|
Total Credit Hours Required for the Major in Statistics | 49-56 | |
Total Credit Hours Required for the BA Degree with a Major in Statistics | 120 |
Degree Requirements
Code | Title | Credit Hours |
---|---|---|
Core Requirements | ||
Mathematics | ||
MATH 101 | SINGLE VARIABLE CALCULUS I | 3 |
or MATH 105 | AP/OTH CREDIT IN CALCULUS I | |
MATH 102 | SINGLE VARIABLE CALCULUS II | 3 |
or MATH 106 | AP/OTH CREDIT IN CALCULUS II | |
Select 1 from the following: | 3 or 6 | |
MULTIVARIABLE CALCULUS | ||
HONORS CALCULUS III and HONORS CALCULUS IV | ||
HONORS MULTIVARIABLE CALCULUS | ||
Select 1 course from the following: | 3 | |
MATRIX ANALYSIS | ||
MATRIX ANALYSIS FOR DATA SCIENCE | ||
LINEAR ALGEBRA | ||
HONORS LINEAR ALGEBRA | ||
Statistical Computation | ||
STAT 405 | R FOR DATA SCIENCE | 3 |
Basic Computing | ||
Select 1 course from the following: | 3-4 | |
INTRODUCTION TO ENGINEERING COMPUTATION | ||
COMPUTATIONAL THINKING | ||
ALGORITHMIC THINKING | ||
Advanced Computing | ||
Select 1 course from the following: | 3-4 | |
INTRODUCTION TO OPERATIONS RESEARCH AND OPTIMIZATION | ||
NUMERICAL ANALYSIS | ||
LINEAR AND INTEGER PROGRAMMING | ||
COMPUTATIONAL SCIENCE | ||
INTRODUCTION TO PROGRAM DESIGN | ||
PRINCIPLES OF PARALLEL PROGRAMMING | ||
TOOLS AND MODELS FOR DATA SCIENCE | ||
REASONING ABOUT ALGORITHMS | ||
INTRODUCTION TO DATA SCIENCE TOOLS AND MODELS | ||
Probability and Statistics | ||
Select 1 course from the following: | 3-4 | |
PROBABILITY AND STATISTICS | ||
HONORS PROBABILITY AND MATHEMATICAL STATISTICS | ||
PROBABILITY AND STATISTICS FOR DATA SCIENCE | ||
STAT 410 | LINEAR REGRESSION | 4 |
Elective Requirements | ||
Select 6 elective courses from departmental (STAT) course offerings at the 300-level or above, including at least 3 courses from the following Methodology/Theory courses: 1 | 18 | |
Methodology/Theory | ||
ADVANCED STATISTICAL METHODS | ||
INTRODUCTION TO STATISTICAL MACHINE LEARNING | ||
PROBABILITY | ||
STATISTICAL INFERENCE | ||
APPLIED TIME SERIES AND FORECASTING | ||
INTRODUCTION TO BAYESIAN INFERENCE | ||
BIOSTATISTICS | ||
NEURAL MACHINE LEARNING I | ||
MULTIVARIATE ANALYSIS | ||
GLM & CATEGORICAL DATA ANALYSIS | ||
Senior Capstone 2 | ||
Select 1 course from the following: | 3-4 | |
APPLIED MACHINE LEARNING AND DATA SCIENCE PROJECTS 3 | ||
SENIOR CAPSTONE PROJECT | ||
Total Credit Hours Required for the Major in Statistics | 49-56 | |
Additional Credit Hours to Complete Degree Requirements * | 33-40 | |
University Graduation Requirements * | 31 | |
Total Credit Hours | 120 |
Footnotes and Additional Information
* | Note: University Graduation Requirements include 31 credit hours, comprised of Distribution Requirements (Groups I, II, and III), FWIS, and LPAP coursework. In some instances, courses satisfying FWIS or distribution requirements may additionally meet other requirements, such as the Analyzing Diversity (AD) requirement, or some of the student’s declared major, minor, or certificate requirements. Additional Credit Hours to Complete Degree Requirements include general electives, coursework completed as upper-level, residency (hours taken at Rice), and/or any other additional academic program requirements. |
1 | With advisor approval, 1 course (3 credit hours) from departments other than Statistics may be used as an elective. The substitution course may not be used as a replacement for 1 of the 3 required methodology/theory courses listed above. STAT 305, STAT 310, STAT 311, STAT 315 and STAT 385 will not count as electives. See below for typically approved coursework. |
2 | The Senior Capstone requirement may not be fulfilled by transfer credit. |
3 | DSCI 435 / COMP 449 is also listed in the Approved Elective category outside departmental (STAT) course offerings. If completed to fulfill the Senior Capstone requirement, this course may not be used as an Approved Elective. |
Approved Electives
With advisor approval, up to 1 course (3-4 credit hours, depending on course selection) from outside departmental (STAT) course offerings may be chosen to fulfill Elective Requirements. The following courses are a sample of approved electives outside Statistics (STAT), however, other courses may be approved by an advisor.
Code | Title | Credit Hours |
---|---|---|
Approved Electives outside Statistics (STAT) | ||
STOCHASTIC MODELS | ||
INTRODUCTION TO OPERATIONS RESEARCH AND OPTIMIZATION 1 | ||
SIMULATION MODELING AND ANALYSIS | ||
STOCHASTIC CONTROL AND APPLICATIONS | ||
PRINCIPLES OF PARALLEL PROGRAMMING 1 | ||
TOOLS AND MODELS FOR DATA SCIENCE 1 | ||
REASONING ABOUT ALGORITHMS 1 | ||
PARALLEL COMPUTING | ||
INTRODUCTION TO DATABASE SYSTEMS | ||
ARTIFICIAL INTELLIGENCE | ||
LARGE-SCALE MACHINE LEARNING | ||
NEURAL MACHINE LEARNING I | ||
INTRODUCTION TO EFFECTIVE DATA VISUALIZATION | ||
APPLIED MACHINE LEARNING AND DATA SCIENCE PROJECTS 2 | ||
GAME THEORY AND OTHER MICRO TOPICS FOR ECON MAJORS | ||
GAME THEORY AND OTHER MICRO TOPICS FOR MTEC MAJORS | ||
MATHEMATICAL ECONOMICS | ||
ECONOMETRICS | ||
ECONOMIC FORECASTING | ||
DATA TOOLS FOR COMPUTATIONAL ECONOMICS | ||
PRINCIPLES OF FINANCIAL ENGINEERING | ||
ADVANCED STATISTICAL METHODS FOR PSYCHOLOGY UNDERGRADUATES | ||
RESEARCH SEMINAR: THE HOUSTON AREA SURVEY | ||
DATA ANALYSIS | ||
INTRODUCTION TO SPORT ANALYTICS | ||
ADVANCED SPORT ANALYTICS |
Footnotes and Additional Information
1 | CMOR 360 (formerly CAAM 378), COMP 322/ELEC 323, COMP 330, and COMP 382 are also listed in the Advanced Computing category. If completed to fulfill Advanced Computing, the course may not be used as an Approved Elective outside Statistics. |
2 | DSCI 435 / COMP 449 is also listed as a Senior Capstone. If completed to fulfill the Senior Capstone requirement, this course may not be used as an Approved Elective. |
Policies for the BA Degree with a Major in Statistics
Program Restrictions and Exclusions
Students pursuing the BA Degree with a Major in Statistics should be aware of the following program restrictions:
-
As noted in Majors, Minors, and Certificates under Declaring Majors, Minors and Certificates, students may not obtain both a BA and a BS in the same major. Students pursuing the BA Degree with a Major in Statistics may not additionally pursue the BS Degree with a Major in Statistics.
- As noted in Majors, Minors, and Certificates, students may not major and minor in the same subject.
- Students pursuing the minor in Data Science may fulfill its requirements according to the following guidelines: i.) DSCI 301 is fulfilled by STAT 310, STAT 311, or STAT 315; ii.) DSCI 302 may be used as the STAT major's Advanced Computing elective; and iii.) DSCI 303 must be substituted with STAT 413.
Transfer Credit
For Rice University’s policy regarding transfer credit, see Transfer Credit. Some departments and programs have additional restrictions on transfer credit. Requests for transfer credit must be approved for Rice equivalency by the designated transfer credit advisor for the appropriate academic department offering the Rice equivalent course (corresponding to the subject code of the course content). The Office of Academic Advising maintains the university’s official list of transfer credit advisors on their website: https://oaa.rice.edu. Students are encouraged to meet with the applicable transfer credit advisor as well as their academic program director when considering transfer credit possibilities.
Departmental Transfer Credit Guidelines
Students pursuing the major in Statistics should be aware of the following departmental transfer credit guidelines:
- No more than 3 courses (9 credit hours) in departmental (STAT) coursework of transfer credit from U.S. or international universities of similar standing as Rice may apply towards the major.
- The Senior Capstone requirement may not be fulfilled by transfer credit.
Additional Information
For additional information, please see the Statistics website: https://statistics.rice.edu/.
Opportunities for the BA Degree with a Major in Statistics
Academic Honors
The university recognizes academic excellence achieved over an undergraduate’s academic history at Rice. For information on university honors, please see Latin Honors (summa cum laude, magna cum laude, and cum laude) and Distinction in Research and Creative Work. Some departments have department-specific Honors awards or designations.
Fifth-Year Master's Degree Option for Rice Undergraduate Students
In certain situations and with some terminal master's degree programs, Rice students have an option to pursue a master’s degree by adding an additional fifth year to their four years of undergraduate studies.
Advanced Rice undergraduate students in good academic standing typically apply to the master’s degree program during their junior or senior year. Upon acceptance, depending on course load, financial aid status, and other variables, they may then start taking some required courses of the master's degree program. A plan of study will need to be approved by the student's undergraduate major advisor and the master’s degree program director.
As part of this option and opportunity, Rice undergraduate students:
- must complete the requirements for a bachelor's degree and the master's degree independently of each other (i.e. no course may be counted toward the fulfillment of both degrees).
- should be aware there could be financial aid implications if the conversion of undergraduate coursework to that of graduate level reduces their earned undergraduate credit for any semester below that of full-time status (12 credit hours).
- more information on this Undergraduate - Graduate Concurrent Enrollment opportunity, including specific information on the registration process can be found here.
Rice undergraduate students completing studies in science and engineering may have the option to pursue the Master of Statistics (MStat) degree. For additional information, students should contact their undergraduate major advisor and the MStat program director.
Internship and Research Opportunities
The Department of Statistics encourages its major and minors to participate the practice of statistics through summer internships, employment and research. Information on current opportunities are posted on the Undergraduate Programs tab of the department website. Students can also approach individual faculty about research opportunities in their group. An undergraduate advisor can talk with you about these and other possibilities.
Additional Information
For additional information, please see the Statistics website: https://statistics.rice.edu/.