Statistics Advising Guide (2022 - 2023)

Click here for the 2021 - 2022 Statistics Advising Guide.

Statistics is the science of collecting, analyzing, and summarizing data. Data is everywhere. When you turn on your mobile phone, take a survey, or purchase groceries you are generating data. As the availability of data grows, so does the need for qualified people to gather, process, and use the data. 

  • Majors receive an in depth exposure to the theory, application and tools needed to be successful inside and outside of the classroom.
  • The interdisciplinary approach taken by the department allows each student to tailor their statistics degree to their own interests.
  • A student graduating from Gustavus with a degree in statistics will have the knowledge and technical skills to find employment in a field of their choosing.

Statistics Major

A grade of C- or higher is required in the 11 courses listed below as well as the successful completion of the cognate requirement. 

  1. MCS-122 Calculus II
  2. One of the following courses in statistics:
    1. MCS-142 Intro to Statistics
    2. E/M-125 Statistics for Economics and Management
    3. PSY 224 Statistics and Research Methods I
  3. MCS-150 Discrete Mathematics
  4. MCS-177 Computer Science I
  5. MCS-222 Multivariate Calculus  
  6.  MCS-240 Statistical Computing and Visualization
  7. MCS-242 Applied Regression Analysis
  8. MCS 243 Design and Analysis of Experiments
  9. MCS-341 Probability Theory and Mathematical Statistics I
  10. MCS-342 Probability Theory and Mathematical Statistics II
  11. One of the following statistics electives
    1. MCS-358 Mathematical Model Building
    2. MCS-354 Advanced Topics in Statistics
    3. An approved internship or summer research opportunity may also be used to satisfy this requirement. Students choosing this latter option should contact their advisor prior to the internship or research experience to complete paperwork and register for MCS 368, if appropriate.
  12. Cognate Requirement: A major in Mathematics or a major or minor in an applied discipline approved by the MCS Department. Examples include Biology, Chemistry, Computer Science, Economics, Environmental Studies, Geography, Geology, Health Fitness, Management, Neuroscience, Physics, Political Science, Psychological Science, and Sociology.

Course Map for Statistics Major

Statistics Minor

  1. One of the following courses in statistics:
    1. MCS-142 Introduction to Statistics
    2. PSY-224 Statistics and Research Methods I
    3. E/M-125 Statistics for Economics and Management
  2. All four of the following courses. 
    • MCS-177 Computer Science I
    • MCS-240 Statistical Computing and Visualization
    • MCS-242 Applied Regression Analysis
    • MCS-243 Design and Analysis of Experiments
  3. A course in research methods in another discipline:
    1. BIO-202 Evolution, Ecology, and Behavior
    2. E/M-355 Marketing Research
    3. E/M-388 Econometrics
    4. ENV-399 Senior Seminar
    5. GEG-242 Research Methods in Geography
    6. GEO-392/393 Research in Geology
    7. HES-220 Research and Statistics in Health and Exercise Science
    8. NUR-202 Research in the Health Sciences
    9. POL-200 Analyzing Politics
    10. PSY-225 Statistics and Research Methods II
    11. S/A-247 Methods of Social Research


  • Potential majors are encouraged to complete the Core courses (MCS-122, MCS-150, MCS-222, MCS-177, MCS-142) by the end of their sophomore year. These courses are offered every semester.
  • MCS-242 and MCS-243 can be taken in any order. 
  • Students who are contemplating graduate study in Statistics are strongly encouraged to double-major in Mathematics.
  • Students interested in a career in actuarial science should have a strong background in mathematics, statistics, and economics. A double major In Statistics and Finance or a major / minor combination is recommended. Students should plan on taking at least the first actuary exam offered by the Society of Actuaries before graduation. See the Actuarial Advising Guide for more details.

Sample Plans

All students should ideally lay out a schedule of their own showing what courses they plan to take, and when they plan to take them. The schedule may not accurately forecast the future, but it is helpful none the less. A printable sample plan can be found on the Statistics Major Form

Starting with Calculus I

Plan for starting with Calc I
  Fall  J Term Spring
1st Year



2nd Year


3rd Year


Cognate minor

Cognate minor
4th Year


Cognate minor


Cognate minor


Starting with Calculus II

Plan for starting with Calc II
  Fall J Term Spring
1st Year MCS-122
2nd Year


3rd Year


Cognate minor


Cognate minor
4th Year


Cognate minor

*MCS-358 MCS-342
Cognate minor


Statistics Course Descriptions

 MCS 114 Introduction to Statistical Literacy (1 course) An introduction to the terminology
and concepts necessary to navigate our data-driven world. Students will learn to be
critically-thinking consumers of data. Topics include sampling and scope of inference,
conditional probabilities, numerical and graphical summaries of data, the basic
concepts behind statistical inference, and ethical practice in statistics and data science.
QUANT, Fall and Spring Semesters.

MCS-142 Introduction to Statistical Methods (1 course) Gathering, organizing, and describing data, probability, random variables, sampling distributions, estimation, and hypothesis testing. Introduction to the use of computerized statistical packages. Students who have already taken a statistics course E/M-125, PSY-224, HES-220, or have received credit from an AP Stats course) may not earn credit for MCS-142. QUANT, Fall and Spring semesters.

MCS-240 Statistical Computing and Visualization (1 course) This course will utilize statistical software packages to learn about the fundamentals of data science needed for data analysis. Topics include data acquisition, data cleaning and wrangling, and visualization techniques. Focus will be on the learned techniques as well as on the communication of findings to a general audience. Prerequisites: MCS-142, E/M-125, or PSY-224. MCS-177 is not required, but highly recommended. QUANT, Fall and Spring

MCS-242 Applied Regression Analysis (1 course) Intermediate course in applied statistics covering simple linear regression, multiple linear regression (with both quantitative and categorical predictors), and logistic regression. Emphasis is on model fitting, diagnostics, inference, and interpretation. Calculations will be done using statistical software and communication of statistical findings will be a major focus. Prerequisite: MCS-240. WRITD, Fall semester.

MCS-243 Design and Analysis of Experiments (1 course) Intermediate course in applied statistics focusing on the fundamentals of experimental design and analysis of variance, which allows for the comparison of group means. In addition to the basic terminology and concepts behind experiments, students will learn about common experimental designs and how to analyze them. Such designs include completely randomized designs, factorial designs, randomized block designs, Latin Squares, and split plots.
Prerequisites: MCS-240. Spring semester.

MCS-341 Probability Theory and Mathematical Statistics I (1 course) The probability model, random variables, conditional probability and independence, probability functions, density functions, expectation, some important discrete and continuous distributions. Prerequisite: MCS-150, MCS-240, and MCS-222. Fall semester.

MCS-342 Probability Theory and Mathematical Statistics II (1 course) Principles of statistical estimation and hypothesis testing using frequentist theory. Additional topics may include Bayesian inference, non-parametric methods, or frequentist inference for regression and/or analysis of variance.Prerequisites: MCS-341. Spring semester. 

MCS-354 Advanced Topics in Statistics An investigation into a branch of statistics not covered elsewhere in the curriculum. The topic will change from year to year, depending on the interests of instructors and students. Prerequisite: permission of instructor. Spring semester of odd years. 

 MCS-358 Mathematical Model Building An introductory study of the formulation of mathematical models to represent, predict, and control real-world situations, especially in the social and biological sciences. The course will use ideas from calculus, linear algebra, and probability theory to describe processes that change in time in some regular manner, which may be deterministic or stochastic. Typical topics are Markov and Poisson processes, discrete and continuous equations of growth, and computer simulation. In addition, students will work on their own mathematical modeling projects. Prerequisites: MCS-177, MCS-122, MCS-221, and MCS-142 or MCS-341. Juniors and Seniors only. January Interim, even years.