Statistics Advising Guide 2024 - 2025

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.
• To declare a Statistics Major, use this form

Statistics Major

Click here for the 2023 - 2024 Statistics Advising Guide.

A grade of C- or higher is necessary in all courses used to satisfy the requirements of the major. 

1. One of the following calculus courses:
   1. MCS-119 Calculus with Pre-Calculus 
   2. MCS-121 Calculus I
2. MCS-122 Calculus II
3. 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
4. MCS-150 Discrete Mathematics
5. MCS-177 Computer Science I
6. MCS-222 Multivariate Calculus  
7.  MCS-240 Statistical Computing and Visualization
8. MCS-242 Applied Regression Analysis
9. MCS 243 Design and Analysis of Experiments
10. MCS-341 Probability Theory and Mathematical Statistics I
11. MCS-342 Probability Theory and Mathematical Statistics II
12. MCS-349 Statistical Consulting
13. MCS-354 Advanced Topics in Statistics

Statistics Minor

A student must successfully complete all 5 of the courses listed below 

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. MCS-177 Computer Science I
3. MCS-240 Statistical Computing and Visualization
4. MCS-242 Applied Regression Analysis
5. MCS-243 Design and Analysis of Experiments

Suggestions

• 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-177 is not a prerequisite for MCS-240, but students are encouraged to take MCS-177 before MCS-240.
• 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

Starting with Calculus II

Statistics Course Descriptions

 MCS 114 Introduction to Statistical Literacy (4 credits) 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 (4 credits) 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 (4 credits) 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 semesters.

MCS-242 Applied Regression Analysis (4 credits) 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 (4 credits) 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 (4 credits) The first in a two-course sequence on the mathematical foundations of statistics. This course focuses on the fundamentals of probability theory. Topics includeThe probability model, random variables, conditional probability and independence, probability functions, density functions, expectation, some important discrete and continuous distributions. Prerequisite: MCS-150, MCS-222, and MCS-240. Fall semester.

MCS-342 Probability Theory and Mathematical Statistics II (4 credits) The second in a two-course sequence on the mathematical foundations of statistics. This course focuses on the pPrinciples 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-349 Statistical Consulting (4 credits) Capstone course for statistics majors that focuses on written and oral communication, collaboration, and teamwork. In this course students will work in small groups to provide statistical consulting services for the campus and greater St. Peter community. Emphasis will be placed on developing written and oral communication skills to communicate statistical results effectively to non-statisticians. Prerequisite: MCS-242, completion or concurrent enrollemtn in MCS-243, and permission of instructor Spring semester, 

MCS-354 Advanced Topics in Statistics (4 credits) 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. Prerequisites: Courses will vary depending on the topic, but all will require MCS-240. Fall semester.