Campuses:
Morris Campus
Statistics B.A.Division of Science & Mathematics  Adm
Division of Science and Mathematics
The mission of the discipline is to create and apply statistical methods for collecting, storing, exploring, analyzing, processing and communicating qualitative/quantitative information and to disseminate this knowledge through teaching, scholarly activity, collaboration and outreach. Statistics is the science and art of enhancing knowledge in the face of uncertainty. In our information age, statistics and data science are central to solving problems in the environment, medicine, law, industry, technology, finance, business, public policy, computing, and science in general. The need for statistics applies to almost every area of our lives. The statistics program provides an operational knowledge of the theory and methods of statistics and the application of statistical methods in a liberal arts environment. It seeks to enhance students' critical thinking in making judgments based on data and provides students with the basic knowledge and skills to make contributions to modern society. Students learn to communicate and collaborate effectively with people in other fields and understand the substance of these fields. The curriculum prepares students to enter graduate school or pursue careers in statistics and data science.
The statistics discipline has the following student learning objectives:
Students will gain the ability to make contributions to society through knowledge of statistical theory and statistics applied to other disciplines.
Students will sharpen their ability to extract useful information from data.
The statistics curriculum will enhance students understanding of the mathematical foundations of statistical theory and methods.
The curriculum will prepare students to enter graduate school, and pursue careers in applied statistics.
Students will be able to communicate statistical ideas and results effectively using presentation skills and visualizations.
The curriculum is designed to ensure that students are able to demonstrate the following outcomes:
Model and solve realworld problems by analyzing them statistically, and determine an appropriate approach towards its solution.
Write, read, and construct proofs of key statistical results
Create estimated models, data displays, and new datasets to address problems using computing tools.
Demonstrate basic knowledge of calculus, analysis, linear algebra, probability, and describe their importance to statistics.
Demonstrate students have background to be employed or gain admission to graduate school.
Meet the requirements for employment in professions such as actuarial science and data science.
Describe and explain a theorem, statistical model, and results of a statistical analysis to a nonspecialist audience.
Program Delivery
This program is available:
Admission Requirements
For information about University of Minnesota admission requirements, visit the
Office of Admissions
website.
General Requirements
All students are required to complete general University and college requirements. For more
information, see the general education requirements.
Program Requirements
Students are required to complete 2 semester(s) of
any second language.
with a grade of C, or better, or S, or demonstrate proficiency in the language(s) as defined by the department
or college.
The GPA in these courses must be at least 2.00. Courses may not be taken SN, unless offered SN only.
Recommended electives for students planning to pursue graduate work in statistics or biostatistics:
MATH 2101  Calculus III
MATH 6111  Linear Algebra
Recommended electives (beyond those listed for graduate work) for students planning to pursue a PhD in statistics or biostatistics:
MATH 2202  Mathematical Perspectives
MATH 3221  Real Analysis I
Required Courses
MATH 1101  Calculus I
[M/SR]
(5.0 cr)
MATH 1102  Calculus II
[M/SR]
(5.0 cr)
STAT 2501  Probability and Stochastic Processes
[M/SR]
(4.0 cr)
STAT 2611  Mathematical Statistics
[M/SR]
(4.0 cr)
STAT 3601  Data Analysis
[M/SR]
(4.0 cr)
STAT 3901  Statistical Communication
(2.0 cr)
STAT 4901  Senior Seminar
(2.0 cr)
Elective Courses
Take 8 or more credit(s) from the following:
·
STAT 1993  Directed Study
(1.05.0 cr)
·
STAT 2701  Introduction to Data Science
[M/SR]
(4.0 cr)
·
STAT 2993  Directed Study
(1.05.0 cr)
·
STAT 3501  Survey Sampling
[M/SR]
(4.0 cr)
·
STAT 3611  Multivariate Statistical Analysis
[M/SR]
(4.0 cr)
·
STAT 3993  Directed Study
(1.05.0 cr)
·
STAT 4601  Biostatistics
(4.0 cr)
·
STAT 4631  Design and Analysis of Experiments
(4.0 cr)
·
STAT 4651  Applied Nonparametric Statistics
(4.0 cr)
·
STAT 4671  Statistical Computing
(4.0 cr)
·
STAT 4681  Introduction to Time Series Analysis
(4.0 cr)
·
STAT 4993  Directed Study
(1.05.0 cr)
Additional Elective Courses
Choose from the list below or from courses with faculty approval.
Take 4 or more credit(s) from the following:
·
CSCI 1201  Introduction to Digital Media Computation
[M/SR]
(4.0 cr)
·
CSCI 1251  Computational Data Management and Manipulation
[M/SR]
(4.0 cr)
·
CSCI 1301  Problem Solving and Algorithm Development
[M/SR]
(4.0 cr)
·
CSCI 1302  Foundations of Computer Science
[M/SR]
(4.0 cr)
·
CSCI 4403  Systems: Data Mining
(2.0 cr)
·
CSCI 4458  Systems: Bioinformatic Systems
(4.0 cr)
·
CSCI 4555  Theory: Neural Networks and Machine Learning
(4.0 cr)
·
ECON 3501  Introduction to Econometrics
[M/SR]
(4.0 cr)
·
GEOG 3501  Geographic Information Systems
[ENVT]
(4.0 cr)
·
GEOL 2161  GIS and Remote Sensing
[SCI]
(4.0 cr)
·
MATH 2101  Calculus III
[M/SR]
(4.0 cr)
·
MATH 2202  Mathematical Perspectives
[M/SR]
(4.0 cr)
·
MATH 3111  Linear Algebra
(4.0 cr)
·
MATH 3221  Real Analysis I
(4.0 cr)
·
MATH 3401  Operations Research
(4.0 cr)
·
MATH 3501  Applied Deterministic Modeling for Management Science
(2.0 cr)
·
MATH 3502  Applied Probabilistic Modeling for Management Science
(2.0 cr)
·
POL 2001  Political Science Research Methods
[SS]
(4.0 cr)
·
PSY 2001  Research Methods in Psychology
[SS]
(4.0 cr)
·
SOC 3103  Research Methodology in Sociology
(4.0 cr)
·
SOC 3131  World Population
[ENVT]
(4.0 cr)


Credits:  5.0 [max 5.0] 
Typically offered:  Every Fall & Spring 
Credits:  5.0 [max 5.0] 
Typically offered:  Every Fall & Spring 
Credits:  4.0 [max 4.0] 
Course Equivalencies:  00927  Math 2501/Stat 2501 
Typically offered:  Periodic Fall 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Fall 
Credits:  2.0 [max 2.0] 
Grading Basis:  AF only 
Typically offered:  Every Spring 
Credits:  2.0 [max 2.0] 
Grading Basis:  SN only 
Typically offered:  Every Fall 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Fall & Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Fall 
Credits:  1.0 5.0 [max 10.0] 
Typically offered:  Every Fall & Spring 
Credits:  4.0 [max 4.0] 
Course Equivalencies:  02221  CSci 2701/Stat 2701 
Prerequisites:  Stat 1601 or Stat 2601 or Stat 2611, CSci 1201 or CSci 1301 or CSci 1251 or # 
Typically offered:  Every Spring 
Credits:  1.0 5.0 [max 10.0] 
Typically offered:  Every Fall & Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Fall Even Year 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Spring 
Credits:  1.0 5.0 [max 10.0] 
Typically offered:  Every Fall & Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Periodic Fall & Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Periodic Fall & Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Periodic Summer 
Credits:  4.0 [max 4.0] 
Typically offered:  Fall Odd Year 
Credits:  1.0 5.0 [max 10.0] 
Typically offered:  Every Fall & Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Fall 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Fall 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Spring 
Credits:  2.0 [max 2.0] 
Typically offered:  Periodic Fall & Spring 
Credits:  4.0 [max 4.0] 
Prerequisites:  3403 or # 
Typically offered:  Periodic Fall & Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Periodic Fall & Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Periodic Fall & Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Fall & Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Fall & Spring 
Credits:  4.0 [max 4.0] 
Prerequisites:  1102, 2202 or # 
Typically offered:  Every Fall 
Credits:  4.0 [max 4.0] 
Prerequisites:  1101 or higher or # 
Typically offered:  Every Spring 
Credits:  2.0 [max 2.0] 
Course Equivalencies:  00924 
Typically offered:  Periodic Fall & Spring 
Credits:  2.0 [max 2.0] 
Course Equivalencies:  00925 
Typically offered:  Periodic Fall & Spring 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Fall 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Fall & Spring 
Credits:  4.0 [max 4.0] 
Prerequisites:  1101 
Typically offered:  Every Fall 
Credits:  4.0 [max 4.0] 
Typically offered:  Every Fall 