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.
 MCS122 Calculus II
 One of the following courses in statistics:
 MCS142 Intro to Statistics
 E/M125 Statistics for Economics and Management
 PSY 224 Statistics and Research Methods I
 MCS150 Discrete Mathematics
 MCS177 Computer Science I
 MCS222 Multivariate Calculus
 MCS240 Statistical Computing and Visualization
 MCS242 Applied Regression Analysis
 MCS 243 Design and Analysis of Experiments
 MCS341 Probability Theory and Mathematical Statistics I
 MCS342 Probability Theory and Mathematical Statistics II
 One of the following statistics electives
 MCS358 Mathematical Model Building
 MCS354 Advanced Topics in Statistics
 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.
 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.
Statistics Minor
 One of the following courses in statistics:
 MCS142 Introduction to Statistics
 PSY224 Statistics and Research Methods I
 E/M125 Statistics for Economics and Management
 All four of the following courses.
 MCS177 Computer Science I
 MCS240 Statistical Computing and Visualization
 MCS242 Applied Regression Analysis
 MCS243 Design and Analysis of Experiments
 A course in research methods in another discipline:
 BIO202 Evolution, Ecology, and Behavior
 E/M355 Marketing Research
 E/M388 Econometrics
 ENV399 Senior Seminar
 GEG242 Research Methods in Geography
 GEO392/393 Research in Geology
 HES220 Research and Statistics in Health and Exercise Science
 NUR202 Research in the Health Sciences
 POL200 Analyzing Politics
 PSY225 Statistics and Research Methods II
 S/A247 Methods of Social Research
 OR ANOTHER APPROVED COURSE
Suggestions
 Potential majors are encouraged to complete the Core courses (MCS122, MCS150, MCS222, MCS177, MCS142) by the end of their sophomore year. These courses are offered every semester.
 MCS242 and MCS243 can be taken in any order.
 Students who are contemplating graduate study in Statistics are strongly encouraged to doublemajor 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
Fall  J Term  Spring  

1st Year 
MCS1221 
MCS122 MCS142 

2nd Year 
MCS222 
MCS243 MCS150 

3rd Year 
MCS242 
MCS354 Cognate minor 

4th Year 
MCS341 
*MCS358 
MCS342 
Starting with Calculus II
Fall  J Term  Spring  

1st Year  MCS122 
MCS222 MCS142 

2nd Year 
MCS240 
MCS150  
3rd Year 
MCS242 
MCS243 Cognate minor 

4th Year 
MCS341 
*MCS358  MCS342 Cognate minor 
Statistics Course Descriptions
MCS 114 Introduction to Statistical Literacy (1 course) An introduction to the terminology
and concepts necessary to navigate our datadriven world. Students will learn to be
criticallythinking 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.
MCS142 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/M125, PSY224, HES220, or have received credit from an AP Stats course) may not earn credit for MCS142. QUANT, Fall and Spring semesters.
MCS240 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: MCS142, E/M125, or PSY224. MCS177 is not required, but highly recommended. QUANT, Fall and Spring
semesters.
MCS242 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: MCS240. WRITD, Fall semester.
MCS243 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: MCS240. Spring semester.
MCS341 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: MCS150, MCS240, and MCS222. Fall semester.
MCS342 Probability Theory and Mathematical Statistics II (1 course) Principles of statistical estimation and hypothesis testing using frequentist theory. Additional topics may include Bayesian inference, nonparametric methods, or frequentist inference for regression and/or analysis of variance.Prerequisites: MCS341. Spring semester.
MCS354 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.
MCS358 Mathematical Model Building An introductory study of the formulation of mathematical models to represent, predict, and control realworld 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: MCS177, MCS122, MCS221, and MCS142 or MCS341. Juniors and Seniors only. January Interim, even years.