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Duluth Campus

Statistics and Actuarial Science B.S.

Mathematics & Statistics
Swenson College of Science and Engineering
  • Program Type: Baccalaureate
  • Requirements for this program are current for Fall 2013
  • Required credits to graduate with this degree: 120
  • Required credits within the major: 56 to 57
  • Degree: Bachelor of Science
The science of statistics is concerned with generating and analyzing data. Actuarial science applies statistical methods to assess risk in the insurance and financial industries. The statistics and actuarial science major prepares students for careers in a wide variety of fields, from banking and government to health care. Advisers have information on the national actuarial examinations. Honors Requirements: To graduate with department honors, a student must complete the program with an overall and department GPA of 3.50, satisfactorily complete a research project under the guidance of a faculty member, and convey research results in a public presentation.
Program Delivery
This program is available:
  • via classroom (the majority of instruction is face-to-face)
Admission Requirements
For information about University of Minnesota admission requirements, visit the Office of Admissions website.
General Requirements
  1. Students must meet all course and credit requirements of the departments and colleges or schools in which they are enrolled including an advanced writing course. Students seeking two degrees must fulfill the requirements of both degrees. However, two degrees cannot be awarded for the same major.
  2. Students must complete all requirements of the Liberal Education Program or its approved equivalent.
  3. Students must complete a minimum of 120 semester credits completed in compliance with University of Minnesota Duluth academic policies with credit limits (e.g., Satisfactory/Non-Satisfactory Grading Policy, Credit for Prior Learning, etc).
  4. At least 30 semester credits must be earned through UMD, and 15 of the last 30 credits earned immediately before graduation must be awarded by UMD.
  5. At least half of upper-division (3xxx-level or higher) credits that satisfy major requirements (major requirements includes all courses required for the major, including courses in a subplan) through UMD.
  6. If a minor is required, students must take at least three upper division credits in their minor field from UMD.
  7. For certificate programs, at least 3 upper-division credits that satisfy requirements for the certificate must be taken through UMD. If the program does not require upper division credits students must take at least one course from the certificate program from UMD.
  8. The minimum cumulative University of Minnesota (UMN) GPA required for graduation is 2.00 and includes only University of Minnesota coursework. A minimum UMN GPA of 2.00 is required in each UMD undergraduate major, minor, and certificate. No academic unit may impose a higher GPA standard to graduate.
  9. Diploma, transcripts, licensure, and certification will be withheld until all financial obligations to the University have been met.
Program Requirements
1. A minor in an area other than mathematics or a second major.
Introduction to Calculus Courses (10 cr)
Calculus I
Take one of the following Calculus I courses:
MATH 1290 - Calculus for the Natural Sciences [LE CAT2, LOGIC & QR] (5.0 cr)
or MATH 1296 - Calculus I [LE CAT, LOGIC & QR] (5.0 cr)
or MATH 1596 {Inactive} [LE CAT2, LOGIC & QR] (5.0 cr)
Calculus II
Take one of the following Calculus II courses:
MATH 1297 - Calculus II [LOGIC & QR] (5.0 cr)
or MATH 1597 {Inactive} [LOGIC & QR] (5.0 cr)
Statistics and Actuarial Science Core Courses (43-44 cr)
CS 1511 - Computer Science I [LE CAT] (5.0 cr)
MATH 3280 - Differential Equations with Linear Algebra (4.0 cr)
MATH 3298 - Calculus III (4.0 cr)
MATH 3355 - Discrete Mathematics (4.0 cr)
MATH 3941 - Undergraduate Colloquium (1.0 cr)
STAT 3611 - Introduction to Probability and Statistics (4.0 cr)
STAT 3612 - Introduction to Probability and Statistics II (3.0 cr)
STAT 5511 - Regression Analysis (3.0 cr)
STAT 5531 - Probability Models (4.0 cr)
STAT 5571 - Probability (4.0 cr)
STAT 5572 - Statistical Inference (4.0 cr)
Take one of the following two courses:
MATH 4201 - Elementary Real Analysis (4.0 cr)
or MATH 4326 - Linear Algebra (3.0 cr)
Advanced Writing Requirement (3 cr)
Advanced Writing - 31xx
 
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MATH 1290 - Calculus for the Natural Sciences (LE CAT2, LOGIC & QR)
Credits: 5.0 [max 5.0]
Course Equivalencies: Math1290/1296/1596
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Differential and integral calculus needed for modeling in earth and life sciences. Computational software. Not intended for students in mathematics, engineering, or physical sciences. prereq: Math ACT 27 or higher or a grade of at least C- in Math 1250 or department consent
MATH 1296 - Calculus I (LE CAT, LOGIC & QR)
Credits: 5.0 [max 5.0]
Course Equivalencies: Math1290/1296/1596
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
First part of a standard introduction to calculus of functions of a single variable. Limits, continuity, derivatives, integrals, and their applications. prereq: Math ACT 27 or higher or a grade of at least C- in Math 1250 or department consent
MATH 1297 - Calculus II (LOGIC & QR)
Credits: 5.0 [max 5.0]
Course Equivalencies: Math 1597/1297
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Second part of a standard introduction to calculus. Vectors, applications of integrals, transcendental functions, series, and multivariable functions and partial derivatives. prereq: A grade of at least C- in 1290 or 1296 or 1596
CS 1511 - Computer Science I (LE CAT)
Credits: 5.0 [max 5.0]
Course Equivalencies: CS 1511/1581
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
A comprehensive introduction to computer programming using the C++ language. The course covers program design, C++ programming basics, control structures, functions and parameter passing. Students write and implement programs with data structures (arrays), pointers and files. Object-oriented programming is also introduced, along with concepts of abstraction, ADTs, encapsulation and data hiding. prereq: 3 1/2 yrs high school math or instructor consent
MATH 3280 - Differential Equations with Linear Algebra
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
First, second, and higher order equations; series methods; Laplace transforms; systems; software; modeling applications; introduction to vectors; matrix algebra, eigenvalues. prereq: A grade of at least C- in 1297 or 1597
MATH 3298 - Calculus III
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Third part of a standard introduction to calculus. Conic sections, vectors and vector-valued functions, partial derivatives and multiple integrals, vector fields, Green's and Stokes' theorems. prereq: A grade of at least C- in 1297 or 1597
MATH 3355 - Discrete Mathematics
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Introduction to mathematical logic, predicates and quantifiers, sets, proof techniques, recursion and mathematical induction, recursive algorithms, analysis of algorithms, assertions and loop invariants, complexity measures of algorithms, combinatorial counting techniques, relations, graph theory. prereq: 1297 or 1597 or instructor consent, a grade of C- or better in is required in all prerequisite courses
MATH 3941 - Undergraduate Colloquium
Credits: 1.0 [max 1.0]
Grading Basis: S-N or Aud
Typically offered: Every Fall, Spring & Summer
Exposure to UMD mathematics-related colloquia. Sixteen points required: one for attending a colloquium; one for writing an acceptable report on a colloquium (at least four must be earned through writing); up to eight for giving a colloquium. prereq: Math major or minor, department consent; must register during semester of 16th point
STAT 3611 - Introduction to Probability and Statistics
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall, Spring & Summer
Basic probability, including combinatorial methods, random variables, mathematical expectation. Binomial, normal, and other standard distributions. Moment-generating functions. Basic statistics, including descriptive statistics and sampling distributions. Estimation and statistical hypothesis testing. prereq: A grade of at least C- in Math 1290 or Math 1296
STAT 3612 - Introduction to Probability and Statistics II
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
An introduction to statistics. Sample distributions, point and interval estimation, hypothesis testing, linear regression, one- and two-way analysis of variance, goodness-of-fit and non-parametric statistics. prereq: 3611 and Math 1297 or equivalent or instructor consent
STAT 5511 - Regression Analysis
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Simple, polynomial, and multiple regression. Matrix formulation of estimation, testing, and prediction in linear regression model. Analysis of residuals, model selection, transformations, and use of computer software. prereq: 3611, Math 3280 or Math 4326, a grade of C- or better in is required in all prerequisite courses
STAT 5531 - Probability Models
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Development of probability models and their applications to science and engineering. Classical models such as binomial, Poisson, and exponential distributions. Random variables, joint distributions, expectation, covariance, independence, conditional probability. Markov processes and their applications. Selected topics in stochastic processes. prereq: 3611, Math 1297 or Math 1597, a grade of C- or better in is required in all prerequisite courses, credit will not be granted if already received for STAT 4531.
STAT 5571 - Probability
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Axioms of probability. Discrete and continuous random variables and their probability distributions. Joint and conditional distributions. Mathematical expectation, moments, correlation, and conditional expectation. Normal and related distributions. Limit theorems. prereq: 3611, Math 3298, a grade of C- or better in is required in all prerequisite courses
STAT 5572 - Statistical Inference
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Spring
Mathematical statistics; Bayes' and maximum-likelihood estimators, unbiased estimators; confidence intervals; hypothesis testing, including likelihood ratio tests, most powerful tests, and goodness-of-fit tests. prereq: STAT 3612 and 5571 with a grade of C- or better, credit will not be granted if already received for STAT 4572
MATH 4201 - Elementary Real Analysis
Credits: 4.0 [max 4.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
In-depth study of concepts fundamental to the theory of single-variable calculus, including topology of the real numbers, convergence of sequences and series, function continuity, the derivative, and the Riemann integral. prereq: 3280, 3355, a grade of C- or better in is required in all prerequisite courses, no grad credit; credit will not be granted if already received for 3299
MATH 4326 - Linear Algebra
Credits: 3.0 [max 3.0]
Grading Basis: A-F or Aud
Typically offered: Every Fall & Spring
Systems of linear equations, matrix algebra, determinants, vector spaces, subspaces, linear independence, span, basis, coordinates, linear transformations, matrix representations of linear transformations, eigenvalues and eigenvectors, diagonalization, Gram-Schmidt orthogonalization, orthogonal projection and least squares. prereq: A grade of at least C- in 3280, 3355, no grad credit