Majors and Minors

Computer Science Major | Computer Science Minor | Mathematics Major | Applied Mathematics and Statistics Major | Mathematics Minor | Statistics Minor | Data Science Minor

General Distribution Requirement

All courses in the department count toward the general distribution requirement in mathematics and natural science except those numbered COMP 154, MATH 212, MATH 614, and MATH 624. Both COMP 154 and MATH 212 count toward the humanities general distribution requirement. MATH 116 is especially appropriate for those students not needing specialized skills or training in mathematics.

General Education Requirements

Courses that meet the general education requirements in writing, quantitative thinking, internationalism and US identities and differences will be posted on the Registrar's web page in advance of registration for each semester.

Additional information regarding the general distribution requirement and the general education requirements can be found in the graduation requirements section of this catalog.

Honors Program

The Mathematics, Statistics, and Computer Science Department participates in the honors program. Eligibility requirements, application procedures, and specific project expectations are available under the MSCS Honors Procedures link on the department web page.

Topics Courses

COMP 194, COMP 294, COMP 394, COMP 494, MATH 194, MATH 294, MATH 394, MATH 494 

Selected topics in mathematics, applied mathematics, and statistics. When the course is offered, the topic and prerequisites for that semester will be announced and posted prior to registration. (4 credits)

Independent Study

The department offers independent study options in the form of tutorials, independent projects, internships, preceptorships and Honors independent projects. For more information contact the department and review the Curriculum section of the catalog.

Computer Science

Program coordinator: Susan Fox

Two basic principles underlie the teaching of computer science at Macalester. First, the program stresses the fundamental principles of computer science-theory of computation, algorithms, languages, software design, and computer organization-as well as programming and the applications of computer technology. A computer science graduate from Macalester will be well prepared for either advanced study or research and development work in industry. Second, the program is firmly committed to the principles and ideals of a liberal arts education. A computer science major or minor includes both technical requirements as well as extensive course work in the humanities, social sciences, and fine arts. An important goal of the program is to produce graduates who are self-educators and life-long learners, characteristics that are so important in a rapidly changing discipline.

Placement

Students seeking an introductory computer science course typically choose among three options: COMP 120, COMP 123, or COMP 124. The first three courses are suitable for students with little or no background in computing, programming, or computer science. All three function as both the first course in the major and minor as well as an introduction to the discipline for those not planning to take further coursework (see below for a brief comparison of the three). Students who have significant prior experience of computer science may choose to enroll in COMP 124 - Object-Oriented Programming and Data Structures. The rare student may begin coursework beyond that point. Students who are uncertain which course to enroll in should contact the program coordinator for advice.

COMP 120 - Computing and Society, is a survey course that provides a broad overview of the discipline of computer science, including the history of computing and the social and ethical concerns raised by information technology. This course is ideal for students in all fields, especially those in the humanities, social sciences, and fine arts. It is also appropriate for potential computer science students who would like their first course to be a survey of the field. COMP 123 - Core Concepts in Computer Science, explores computer science through a set of core ideas, theoretical and practical, such as design, implementation, and analysis of algorithms, and common data representations. Currently this course uses applications from media computation and robotics to motivate the central ideas. This course is ideal for students who want to begin with an examination of the fundamental conceptual issues of computer science.

Topics Courses

COMP 194, COMP 294, COMP 394, COMP 494 

Topics of interest to students in the field of computer science but which are not part of the regular curriculum. When the course is offered, the topic and prerequisites for that semester will be announced and posted prior to registration. (4 credits)

Independent Study

The department offers independent study options in the form of tutorials, independent projects, internships, preceptorships and Honors independent projects. For more information contact the department and review the Curriculum section of the catalog.

Computer Science Major

Major Requirements

  1. Introductory sequence:
    • One of the three introductory courses COMP 120 or COMP 123. A student may not receive credit towards the major for more than one of these courses. Students who pass out of these courses typically begin the major with COMP 124.
    • The introductory course COMP 124.
  2. Core courses: the four required core courses COMP 221, COMP 225, COMP 240, and COMP 261.
  3. Elective courses: A minimum of three advanced elective courses in computer science, numbered 300-500,excluding COMP 490.
  4. Supporting courses: MATH 136 and any two additional mathematics courses taken at Macalester and approved by the department. Courses which are highly appropriate for computer science majors would include: MATH 135, MATH 137, MATH 155, MATH 236, MATH 313.
  5. Capstone: The College's capstone graduation requirement in Computer Science is satisfied by:

    - passing an approved capstone course (COMP 342, COMP 346, COMP 380, COMP 440, COMP 445, COMP 469, COMP 484) or passing an Independent Study associated with an Honors thesis, and
    - giving a public presentation of your work to a general audience on Capstone Day in April, and
    - participating in all departmental senior capstone meetings

     The capstone course must be taken junior year or fall of senior year. Each course designated as such will include a serious semester project, and each Computer Science  major must pass the project part of the class.

In addition to the three required mathematics courses, students are strongly encouraged to include some of the following courses as part of their elective program: MATH 155 - Introduction to Statistical Modeling, MATH 236 - Linear AlgebraMATH 253 - Statistical Computing and Machine Learning, MATH 254 - Probability and Mathematical Statistics, MATH 313 - Advanced Symbolic Logic, MATH 455 - Mathematical Statistics, and MATH 432 - Mathematical Modeling.

Students who plan to attend graduate school in computer science are encouraged to take more than the minimum number of computer science electives as well as additional supporting work in related disciplines. In order to ensure orderly progress through the curriculum, introductory courses (COMP 120 or COMP 123, COMP 124) and core courses (COMP 221, COMP 225, COMP 240, and COMP 261) should generally be completed before a student enrolls in advanced electives or begins an independent project.

A typical computer science major would take the following courses toward the major in the first two years:

Year 1: COMP 120 or COMP 123, COMP 124; MATH 136; a second mathematics course
Year 2: COMP 225; COMP 221; COMP 240; COMP 261; a mathematics course

However, there is a good deal of flexibility in the computer science program, and a student's exact schedule will be determined only after consultation with his or her major advisor.

Computer Science Minor

Minor Requirements

Requirements for a minor in computer science are:

Any five courses in computer science numbered 120-489. Minor plans including more than one crosslisted course require departmental approval. (Note: Credit can be awarded for only one of the introductory courses COMP 120 or COMP 123.)

No more than two courses can count toward any other minor or major.

Mathematics Major

Major Requirements

Students earn a major in Mathematics by choosing between two paths: Mathematics or Applied Mathematics and Statistics.

Requirements for Mathematics are:

  1. Discrete Mathematics: the introductory course MATH 136. Exceptionally well-prepared students may replace this course with a second course from 3 or 4, below.
  2. Linear Algebra and Multivariable Calculus: the two courses MATH 236 and MATH 237. We recommend that these be completed by the end of the sophomore year.
  3. Discrete Core: At least one of: MATH 373, MATH 376, MATH 379.
  4. Continuous Core: At least one of: MATH 312, MATH 371, MATH 377.
  5. Depth Course: At least one of the following, which must be taken at Macalester: MATH 432, MATH 437, MATH 469, MATH 471, MATH 476, MATH 477, MATH 478 .
  6. Elective: At least two other Mathematics course numbered MATH 254, 300-489, or MATH 494.
  7. Supporting Courses:
    • A Computer Science course that is not cross-listed as a Mathematics course. We recommend that this course be taken by the end of the sophomore year.
    • The statistics course MATH 155.
  8. Capstone: The College's capstone graduation requirement in Mathematics will be satisfied by
    • passing an approved capstone course (MATH 353, MATH 355 , MATH 373, MATH 432, MATH 437, MATH 469, MATH 471, MATH 476, MATH 477, or MATH 478) or registering for an Independent Study associated with an Honors thesis, and
    • giving a public presentation of your work to a general audience on Capstone Day in April.
    • The capstone course must be taken junior or senior year. Each course designated as such will include a serious semester project, and each math major must pass the project part of the class. Additionally, each capstone-designated course will require students to attend at least two departmental seminars.

Note to students preparing for graduate work in mathematics: You should take MATH 376, MATH 377, and several courses chosen from MATH 471, MATH 476, MATH 477, MATH 478. Take the GREs during the fall of your senior year.

Requirements in Applied Mathematics and Statistics are:

An Applied Mathematics and Statistics major consists of at least nine courses.

  1. The three introductory courses: MATH 155 (S), MATH 236 , and MATH 237 .
  2. At least five intermediate or advanced courses, chosen from this list:
  3. Two or more courses with a Computation (C) designation:
  4. Three or more courses with a Statistical (S) designation, which may meet other requirements of the major.
  5. Integrative Experience in the form of at least one of the following:
    • An internship or summer research project approved by the department;
    • A minor or major in another department tied to applied mathematics or statistics (e.g., physics, economics, psychology, sociology, chemistry, biology, geology, geography, environmental studies, computer science) approved on a case-by-case basis by the department.
    • A preceptorship in two of the courses included in the applied mathematics requirement;
  1. Capstone: The College's capstone graduation requirement in Applied Mathematics will be satisified by
    • passing an approved capstone course (MATH 353, MATH 355 , MATH 432MATH 437, MATH 469, or other capstone courses as approved by the department on a case-by-case basis) or registering for an Independent Study associated with an Honors thesis, and
    • giving a public presentation of your work to a general audience on Capstone Day in April.
    • The capstone course must be taken junior or senior year. Each course designated as such will include a serious semester project, and each AMS major must pass the project part of the class. Additionally, each capstone-designated course will require students to attend at least two departmental seminars. The capstone-designated course may meet other requirements of the Applied Mathematics and Statistics major.

Note to students preparing for graduate work: You should plan your major with consideration of the entrance requirements for your specific field in consultation with a faculty member in the department. Take the GREs during the fall of your senior year.

Mathematics Minor

To obtain a minor in mathematics, you must complete the following:

  1. MATH 136, MATH 236, MATH 237 and at least 8 semester credits from Mathematics courses numbered 300-489, except topics courses unless prior departmental approval has been given.
  2. COMP 123 or an equivalent course.

No more than two courses can count toward any other minor or major.

Statistics Minor

Minor Requirements

To obtain a minor in statistics, you must complete the following:

COMP 123 or an equivalent course; MATH 155; and any 3 of the following: MATH 253 - Statistical Computing and Machine Learning , MATH 254 - Probability and Mathematical Statistics, MATH 353 - Survival Analysis, MATH 355.

No more than two courses can count toward any other minor or major.

Students preparing for graduate work in statistics are also encouraged to take MATH 236 and MATH 237.

Data Science Minor

The requirements for the minor are as follows:

Two courses in each of the three areas below.

  1. Computing
    *COMP 123 - Core Concepts in Computer Science AND
    * One of: COMP 124 - Object-Oriented Programming and Data Structures or COMP 302 - Introduction to Database Management Systems or COMP 365 - Computational Linear Algebra or COMP 440 - Collective Intelligence or COMP 484 - Introduction to Artificial Intelligence, or others as approved by the department.
  2. Statistics
    *MATH 155 - Introduction to Statistical Modeling AND
    *One of: MATH 253 - Statistical Computing and Machine Learning or MATH 353 - Survival Analysis or MATH 355 - Bayesian Statistics, or others as approved by the department.
  3. Domain area expertise
    * Two courses in a single domain meeting the following criteria: the courses should be focused around a theme (e.g., bioinformatics) and not a broad discipline AND that theme should
       one that allows the possibility of data science-related activities, either within the courses themselves or in the student's future career or further education.
    * Pre-approved domain courses are listed below. Proposals for other areas of domain expertise (supported by two courses) will be approved on a case by case basis by the department.

No more than two courses can count toward any other major or minor.
Applied Mathematics and Statistics Majors may not also earn a Data Science Minor.

To ensure a synthesis between coursework in the department and the domain of expertise, all students must complete an integrative essay that either a) discusses an already completed integrative project (a course project, internship, summer research experience, etc), or b) proposes an integrative project in the domain of expertise.

Pre-Approved Domain Courses

Astronomy
PHYS 120 - Astronomical Techniques and
PHYS 440 - Observational Astronomy

Bioinformatics
BIOL 260 - Genetics and COMP 320 - Computational Biology 

Data-Driven Journalism
MCST 114 - News Reporting and Writing and one of the following:
MCST 355 - Advanced Journalism: Electronic 
MCST 357 - Advanced Journalism: New Media 

Ecology
BIOL 285 - Ecology and one of the following:
BIOL 342 - Animal Behavior/Ecology 
BIOL 344 - Aquatic Ecology 
BIOL 345 - Field Botany 

Environmental Science and Policy
ENVI 231 - Environmental Economics and Policy and one of the following:
ENVI 130 - Science of Renewable Energy
ENVI 140 - The Earth's Climate System
ENVI 150 - Climate and Society
ENVI 160 - Dynamic Earth and Global Change 

Geographic Analytics
GEOG 225 - Introduction to Geographic Information Systems and one of the following:
GEOG 262 - Metro Analysis
GEOG 362 - Introduction to Remote Sensing
GEOG 364 - GIS and Community Partnerships 
GEOG 365 - Urban GIS
GEOG 366 - GIS for Global Urban Environments
GEOG 367 - Environmental Geographic Information Systems (GIS)
GEOG 368 - Health GIS
GEOG 378 - Statistical Research Methods in Geography 

Neuroscience
NEUR 244 - Cognitive Neuroscience and NEUR 385 - Mind Reading: Understanding Functional Magnetic Resonance Imaging 

Political Analytics
POLI 214 - Cyber Politics and POLI 269 - Empirical Research Methods 

Quantitative Economics
Two of the following:
ECON 358 - Introduction to Securities Analysis 
ECON 381 - Introduction to Econometrics 
ECON 420 - Quantitative Macroeconomic Analysis 
ECON 485 - Empirical Finance 

Quantitative Public Health
Two of the following:
BIOL 355 - Virology 
BIOL 357 - Immunology 
GEOG 256 - Medical Geography 
MATH 125 - Epidemiology