Statistics

This degree option differs from the BA in Mathematics without an option only in the Option Requirements.

Bachelor of Arts - Mathematics; Statistics Option

College Humanities & Sciences

Catalog Year: 2016-2017

Degree Specific Credits: 67

Required Cumulative GPA: 2.0

Note: The degree specific credits are much lower for double-majors and for students completing an additional minor (in another subject): 41 credits for students completing a second major, and 46 credits for students completing a minor.

Mathematics Core Courses

Minimum Required Grade: C-
23 Total Credits Required

Calculus I

Rule: Take 1 of the following 2 courses.

Show All Course Descriptions Course Credits
Show Description M 171 - Calculus I
Offered autumn and spring. Prereq., M 122 or 151 or ALEKS placement >= 5.  Differential calculus, including limits, continuous functions, Intermediate Value Theorem, tangents, linear approximation, inverse functions, implicit differentiation, extreme values and the Mean Value Theorem.  Integral Calculus including antiderivatives, definite integrals, and the Fundamental Theorem of Calculus.
 4 Credits
Show Description M 181 - Honors Calculus I
Offered autumn.  Prereq., consent of instr.  Coreq., Honors Calculus Seminar, a section of M 294.  Honors version of M 171.
 4 Credits
Minimum Required Grade: C- 4 Total Credits Required

Calculus II

Rule: Take 1 of the following 2 courses.

Show All Course Descriptions Course Credits
Show Description M 172 - Calculus II
Offered autumn and spring. Prereq., M 171 or 181. Techniques of Integration. Area computations. Improper integrals. Infinite series and various convergence tests. Power series. Taylor's Formula. Polar coordinates. Parametric curves.
 4 Credits
Show Description M 182 - Honors Calculus II
Offered spring.  Prereq., M 181 or consent of instr.  Coreq., Honors Calculus Seminar, a section of M 294.  Honors version of M 172.
 4 Credits
Minimum Required Grade: C- 4 Total Credits Required

Other Mathematics Core Courses

Rule: Take all of the following courses.

Show All Course Descriptions Course Credits
Show Description M 210 - Intro to Mathematical Software
Offered spring. Prereq., one of M 162, 171, or 181, or consent of instr. Software packages useful for doing and writing mathematics. Introduction to a computer algebra system (such as Maple or Mathematica), a numerical package (such as MATLAB or R), and elementary programming. Writing and communicating mathematics using the mathematical typesetting system LaTeX.
 3 Credits
Show Description M 221 - Introduction to Linear Algebra
Offered autumn and spring. Prereq., M 172 or 182. Vectors in the plane and space, systems of linear equations and Gauss–Jordan elimination, matrices, determinants, eigenvalues and eigenvectors, vector spaces, linear transformations. Calculators and/or computers used where appropriate.
 4 Credits
Show Description M 273 - Multivariable Calculus
Offered autumn and spring. Prereq., M 172 or 182. Calculus of functions of several variables; differentiation and elementary integration. Vectors in the plane and space.
 4 Credits
Show Description M 300 - Undergraduate Mathematics Sem
(R–6) Offered every semester. Prereq., M 171 or 181. Discussion seminar focused on topics and issues of interest to students in the mathematical sciences.
 1 Credits
Show Description M 307 - Intro to Abstract Mathematics
Offered autumn and spring. Prereq., M 172 or 182. Designed to prepare students for upper–division proof–based mathematics courses. Topics include proof techniques, logic, sets, relations, functions and axiomatic methods. Students planning to take both M 221 and 307 are encouraged to take M 221 first.
 3 Credits
Minimum Required Grade: C- 15 Total Credits Required

Upper-Division Mathematics Requirement

Rule: Take 23 credits in this category.

Note: (1) Students completing a minor (in another subject) need take only 20 credits.
(2) Students completing a second major need take only 18 credits.

Minimum Required Grade: C-
23 Total Credits Required

Upper-Division Elective Courses

Rule: Take 7 courses from the following list; at least 3 of them must be at the 400 level.

Note: (1) Students completing a minor (in another subject) or a second major need take only 6 courses (totaling 18 credits or more).
(2) Residency Requirement: At least 4 of the courses in this category must be taken at UM-Missoula (only 3 if M 307 is taken at UM-Missoula).
(3) Note that STAT 451 does not count toward this requirement.

Show All Course Descriptions Course Credits
Show Description M 301 - Math Technology for Teachers
Offered autumn. Prereq., M 221. Discrete and continuous mathematical models from a variety of disciplines using appropriate technology.
 3 Credits
Show Description M 311 - Ordinary Diff Equations/System
Offered autumn. Prereq., M 273. Ordinary differential equations. Systems of linear differential equations from a matrix viewpoint.  Series solutions. Existence and uniqueness for initial value problems.  Numerical methods. Stability and selected topics. M 317 computer lab recommended.
 3 Credits
Show Description M 325 - Discrete Mathematics
Offered spring. Prereq., M 171 and 225 or 307. Continuation of 225 and topics from graph theory, Boolean algebras, automata theory, coding theory, computability and formal languages.
 3 Credits
Show Description M 326 - Number Theory
Offered spring. Prereq., M 225 or 307. Congruences, Diophantine equations, properties of primes, quadratic residues, continued fractions, algebraic numbers.
 3 Credits
Show Description M 361 - Discrete Optimization
Offered spring. Prereq., one of M 162, 172 or 182 (221 or 225 recommended). Intended for non–mathematics majors as well as mathematics majors. Introduction to discrete optimization and modeling techniques with applications. Topics from combinatorics and graph theory, including enumeration, graph algorithms, matching problems and networks.
 3 Credits
Show Description M 362 - Linear Optimization
Offered autumn. Prereq., one of M 162, 172 or 182 (221 recommended). Coreq., M 363 recommended. Intended for non–mathematics majors as well as majors. Introduction to linear programming and modeling techniques with applications. Topics include the simplex method, duality, sensitivity analysis and network models.
 3 Credits
Show Description M 381 - Advanced Calculus I
Offered autumn .  Prereq., M 307.  Rigorous development of single-variable calculus with formal proof.  Functions, sequences, limits, continuity, differentiation, and integration.
 3 Credits
Show Description M 412 - Partial Differential Equations
Offered spring. Prereq., M 311. Fourier series, Sturm–Liouville and boundary value problems. Partial differential equations: Cauchy problems and the method of characteristics, separation of variables and Laplace transform methods. Numerical methods and selected topics. M 418 computer lab recommended. Level: Undergraduate-Graduate
 3 Credits
Show Description M 414 - Deterministic Models
Offered spring. Prereq., M 263 or 311 or consent of instr. Linear and nonlinear difference and differential equations: stability, phase–plane analysis, oscillatory behavior, limit cycles, and chaos. Eigenvalues and eigenfunctions. Emphasis on models in biology. Level: Undergraduate-Graduate
 3 Credits
Show Description M 429 - History of Mathematics
Offered spring. Prereq., M307. Historical study of the development of mathematics from the Egyptian and Babylonian eras to the 20th century. Level: Undergraduate-Graduate
 3 Credits
Show Description M 431 - Abstract Algebra I
Offered autumn. Prereq., M 221 and 307 or consent of instr. An introduction to modern ideas of algebra through the study of groups, rings, and fields. Level: Undergraduate-Graduate
 4 Credits
Show Description M 432 - Abstract Algebra II
Offered spring. Prereq., M 431. Continues the investigation of groups, rings, and fields begun in M 431. Further topics include vector spaces and field extensions. Level: Undergraduate-Graduate
 4 Credits
Show Description M 439 - Euclidean & Non-Euclidean Geo
Offered autumn. Prereq., M 307. Euclidean geometry from a rigorous, axiomatic viewpoint and Non–Euclidean geometries chosen from Lobachevskian, projective, finite and Riemannian. Level: Undergraduate-Graduate
 3 Credits
Show Description M 440 - Numerical Analysis
Offered intermittently. Prereq., 311, one computer language. Error analysis; approximation and interpolation, numerical solution of linear and non-linear equations, numerical integration of ordinary and partial differential equations. Level: Undergraduate-Graduate
 4 Credits
Show Description M 445 - Stat/Math/Comp Modeling
Offered autumn odd-numbered years. Prereq., consent of instr. An interdisciplinary course on the integration of statistical and dynamical models with applications to biological problems. Linear and nonlinear models, estimation, systems of ordinary differential equations, numerical integration, bootstrapping, MCMC methods. Intended both for students in mathematics and the natural sciences. Level: Undergraduate-Graduate
 4 Credits
Show Description M 461 - Practical Big Data Analytics
Offered autumn. Prereq., STAT 341, and one of M 221 or M 273, or consent of instructor. This is a methods course supporting the Big Data Certificate Program. The course provides the students with the essential tools for the analysis of big data. The content consists of map reduce and canonical information methods for analyzing massively large data sets, windowing methods for the analysis of streaming data, an introduction to predictive analytics, and an introduction to data visualization methods. Level: Undergraduate-Graduate
 3 Credits
Show Description M 462 - Theoretical Big Data Analytics
Offered spring. Prereq., M 221 and two other Mathematics / Statistics classes at the 200-level or above, or consent of instr. The main goal of this course is to provide students with a unique opportunity to acquire conceptual knowledge and theoretical background behind mathematical tools applicable to Big Data Analytics and Real Time Computations. Specific challenges of Big Data Analytics, e.g., problems of extracting, unifying, updating, and merging information, and processing of highly parallel and distributed data, will be reviewed. The tools for Big Data Analytics, such as regression analysis, linear estimation, calibration problems, real time processing of incoming (potentially infinite) data, will be studied in more detail. It will be shown how these approaches can be transformed to conform to the Big Data demands. Level: Undergraduate-Graduate
 3 Credits
Show Description M 472 - Intro to Complex Analysis
Offered spring. Prereq., M 273, M 307. Analytic functions, complex integration, singularities and application to contour integration, harmonic functions, spaces of analytic functions. Level: Undergraduate-Graduate
 4 Credits
Show Description M 473 - Introduction to Real Analysis
Offered autumn odd-numbered years. Prereq., M 273, M 307. Theory of metric spaces and point set topology, Riemann-Stieltjes integral, sequences and series of functions. Stone-Weierstrass theorem, theorem of Arzela-Ascoli, introduction to Lebesgue integration. Level: Undergraduate-Graduate
 4 Credits
Show Description M 485 - Graph Theory
Offered autumn. Prereq., M 325, or M 307 and M 361, or consent of instr. Theory and applications of graphs. Topics chosen from trees, matchings, connectivity, coloring, planarity, Ramsey theory, random graphs, combinatorial designs and matroid theory. Level: Undergraduate-Graduate
 3 Credits
Show Description STAT 341 - Intro to Probability and Stat
Offered autumn and spring. Prereq., one of M 162, 172 or 182. Probability, probability models and simulation, random variables, density functions, special distributions, and a brief survey of estimation and hypothesis testing. Computer use integrated throughout.
 3 Credits
Show Description STAT 421 - Probability Theory
Offered autumn. Prereq., M 273 or consent of instructor (STAT 341 recommended). An introduction to probability, random variables and their probability distributions, estimation and hypothesis testing. This course is the foundation on which more advanced statistics courses build. Level: Undergraduate-Graduate
 3 Credits
Show Description STAT 422 - Mathematical Statistics
Offered spring. Prereq., STAT 421. Continuation of 421. Level: Undergraduate-Graduate
 3 Credits
Show Description STAT 452 - Statistical Methods II
Offered spring. Prereq., STAT 451. Continuation of STAT 451. May not be counted toward a major in mathematics. Multiple regression, experimental design, analysis of variance, other statistical models. Level: Undergraduate-Graduate
 3 Credits
Minimum Required Grade: C- 21 or more Total Credits Required

Upper-Division Elective Computer Labs

Rule: Computer labs from the following list are optional; if taken, they count toward the total number of credits required for the Upper-Division Mathematics Requirement.

Show All Course Descriptions Course Credits
Show Description M 317 - ODE Computer Lab
Offered autumn.  Coreq., M 311 or consent of instr.  Intended primarily for student in M 311.
 1 Credits
Show Description M 363 - Linear Optimization Lab
Offered autumn.  Coreq., M 362.  Introduction to linear optimization software.
 1 Credits
Show Description M 418 - PDE Computer Lab
Offered spring. Coreq., M 412 or consent of instr. Intended primarily for students in M 412. Level: Undergraduate-Graduate
 1 Credits
Show Description STAT 457 - Computer Data Analysis I
Offered autumn. Coreq., STAT 451 or consent of instr. An introduction to software for doing statistical analyses. Intended primarily for students in STAT 451. Level: Undergraduate-Graduate
 1 Credits
Show Description STAT 458 - Computer Data Analysis II
Offered spring. Coreq., STAT 452 or consent of instr. Continuation of STAT 457. Intended primarily for students in STAT 452. Level: Undergraduate-Graduate
 1 Credits
Minimum Required Grade: C- 0-5 Total Credits Required

Science Requirement

Rule: Take 18 credits in at most 3 areas selected from astronomy (ASTR), biology (BIO*), chemistry (CHMY), computer science (CSCI, except CSCI TR*), economics (ECNS), forestry (FORS, WILD), geosciences (GEO), management information systems (BMIS), and physics (PHSX).

Note: (1) Students completing a minor (in another subject) or a second major are exempt from this requirement.
(2) Transfer courses listed on the transcript as “CSCI TR*” may include course work in other areas such as Computer Applications (CAPP) and therefore do not count towards this requirement unless a student successfully petitions the Department of Mathematical Sciences.

Minimum Required Grade: C-
18 Total Credits Required

Advanced College Writing Requirement

Rule: Take 1 of the following 2 courses, or any other approved Advanced College Writing course.

Show All Course Descriptions Course Credits
Show Description M 429 - History of Mathematics
Offered spring. Prereq., M307. Historical study of the development of mathematics from the Egyptian and Babylonian eras to the 20th century. Level: Undergraduate-Graduate
 3 Credits
Show Description M 499 - Senior Thesis
(R–12) Offered autumn and spring. Prereq., consent of instr. Senior thesis for mathematics majors and/or Watkins Scholars.
 1 To 12 Credits
Minimum Required Grade: C- 3 Total Credits Required

GPA Requirement

Note: (1) A cumulative GPA of 2.0 is required for all courses used to fulfill major requirements.
(2) In addition, a cumulative GPA of 2.0 is required for all mathematical sciences courses used to fulfill major requirements. (Mathematical sciences courses are those with a prefix of M or STAT.)

Foreign Language/Computer Science Requirement

Rule: Either complete the General Education Requirement "Group III: Modern and Classical Language" (not the symbolic systems exception), or take one course from the following list.

Note: Students completing a second major are exempt from this requirement.

Show All Course Descriptions Course Credits
Show Description CSCI 100 - Intro to Programming
Offered autumn and spring. This course covers basic programming concepts such as variables, data types, iteration, flow of control, input/output, functions, and objects. The course will also cover programming ideas such as data structures, algorithms, modularity, and debugging. Students will learn about the role computation can play in solving problems by writing interesting programs to solve useful goals. No prior programming experience is expected. (Two hours independent lab per week.) Credit not allowed for both CSCI 100 and CSCI 110.
 3 Credits
Show Description CSCI 135 - Fund of Computer Science I
Offered autumn and spring. Prereq., computer programming experience in a language such as BASIC, Pascal, C, etc. Fundamental computer science concepts using the high level structured programming language, Java.
 3 Credits
Show Description CSCI 136 - Fund of Computer Science II
Offered autumn and spring. Prereq., CSCI 135; coreq., M 115 or M 151 or consent of instr. Continuation of CSCI 135. Survey of computer science topics including recursion, algorithms, basic data structures, operating systems, artificial intelligence, graphics, user interfaces, and social and ethical implications of computing.
 3 Credits
Show Description CSCI 250 - Computer Mdlng/Science Majors
Offered autumn. Prereq., basic computer and spreadsheet literacy; coreq., M 162 or 171.  An introduction to programming in Python with an emphasis on problems arising in the sciences, including: function plotting, data fitting, file input/output, solving ordinary differential equations, matrix manipulation, and sensor networks. A student can take at most one of CSCI 172, CSCI 250, CRT 280, and CRT 281 for credit.
 3 Credits
Minimum Required Grade: C- 3 Total Credits Required

Requirements for the Statistics Option

Rule: Take 4 of the following courses

Note: Additional mathematics and statistics courses chosen with advisor.

Show All Course Descriptions Course Credits
Show Description M 461 - Practical Big Data Analytics
Offered autumn. Prereq., STAT 341, and one of M 221 or M 273, or consent of instructor. This is a methods course supporting the Big Data Certificate Program. The course provides the students with the essential tools for the analysis of big data. The content consists of map reduce and canonical information methods for analyzing massively large data sets, windowing methods for the analysis of streaming data, an introduction to predictive analytics, and an introduction to data visualization methods. Level: Undergraduate-Graduate
 3 Credits
Show Description M 462 - Theoretical Big Data Analytics
Offered spring. Prereq., M 221 and two other Mathematics / Statistics classes at the 200-level or above, or consent of instr. The main goal of this course is to provide students with a unique opportunity to acquire conceptual knowledge and theoretical background behind mathematical tools applicable to Big Data Analytics and Real Time Computations. Specific challenges of Big Data Analytics, e.g., problems of extracting, unifying, updating, and merging information, and processing of highly parallel and distributed data, will be reviewed. The tools for Big Data Analytics, such as regression analysis, linear estimation, calibration problems, real time processing of incoming (potentially infinite) data, will be studied in more detail. It will be shown how these approaches can be transformed to conform to the Big Data demands. Level: Undergraduate-Graduate
 3 Credits
Show Description STAT 341 - Intro to Probability and Stat
Offered autumn and spring. Prereq., one of M 162, 172 or 182. Probability, probability models and simulation, random variables, density functions, special distributions, and a brief survey of estimation and hypothesis testing. Computer use integrated throughout.
 3 Credits
Show Description STAT 421 - Probability Theory
Offered autumn. Prereq., M 273 or consent of instructor (STAT 341 recommended). An introduction to probability, random variables and their probability distributions, estimation and hypothesis testing. This course is the foundation on which more advanced statistics courses build. Level: Undergraduate-Graduate
 3 Credits
Show Description STAT 422 - Mathematical Statistics
Offered spring. Prereq., STAT 421. Continuation of 421. Level: Undergraduate-Graduate
 3 Credits
Show Description STAT 452 - Statistical Methods II
Offered spring. Prereq., STAT 451. Continuation of STAT 451. May not be counted toward a major in mathematics. Multiple regression, experimental design, analysis of variance, other statistical models. Level: Undergraduate-Graduate
 3 Credits
Minimum Required Grade: C- 12 Total Credits Required