Offered at: San Luis Obispo Campus
The statistics degree program requires students to develop a strong foundation in mathematics, computer science, and communication. Coursework in the statistics program can be classified into four areas. Some courses provide mathematical background in probability and theoretical statistics. Others focus on computational thinking and coding skills with software packages. Most courses teach particular statistical methods for various types of data analysis such as regression, experimental design, categorical data analysis, time series techniques, multivariate methods, and survival analysis. Finally, some courses specifically develop students' skills with oral and written communication and consulting with clients.
Throughout the program students encounter the entire process of conducting statistical investigations, from asking questions and designing studies through drawing conclusions and communicating results. Statistics students repeatedly process and analyze real data from genuine studies and also acquire extensive experience coding, using statistical software, and writing technical reports of their analyses and findings for varied audiences.
Program Learning Objectives
- Have good working knowledge of the most commonly used statistical methods, including statistical modeling and omnipresent role of variability, efficient design of studies and construction of effective sampling plans, exploratory data analysis, and formal inference process.
- Have background in probability, statistical theory, and mathematics, including especially calculus, linear algebra and symbolic and abstract thinking.
- Be able to synthesize and apply knowledge of common inferential methods, understanding the limitations of procedures and appropriate conclusions.
- Communicate effectively (written and oral) with skills in collaboration (within and between disciplines) and teamwork, and in organizing and managing projects.
- Have a good mastery of several standard statistical software packages and facility with data management strategies.
- Have a focused concentration in an area of application outside the discipline of statistics.
Degree Requirements and Curriculum
In addition to the program requirements listed on this page, students must also satisfy requirements outlined in more detail in the Minimum Requirements for Graduation section of this catalog, including:
- 40 units of upper-division courses
- 2.0 GPA
- Graduation Writing Requirements (GWR)
- U.S. Cultural Pluralism (USCP)
Note: No course with a STAT prefix may be selected as credit/no credit. In addition, no more than 12 units of cooperative or internship courses can count towards your degree requirements.
| Code | Title | Units |
|---|---|---|
| MAJOR COURSES | ||
| DATA 1000 | Statistical and Data Literacy (2) 1 | 3 |
| DATA/STAT 1810 | Introduction to Statistical Computing with R | 3 |
| DATA/STAT 3820 | Intermediate Statistical Computing with R | 3 |
| STAT 1510 | Statistics I | 3 |
| STAT 2610 | Introduction to Probability and Simulation | 3 |
| STAT 3520 | Statistics II | 3 |
| STAT 3530 | Applied Linear Models | 4 |
| STAT 3540 | Statistical Methods for Study Design and Analysis | 4 |
| DATA/STAT 3800 | Introduction to Statistical Computing with SAS and SQL | 3 |
| or DATA 3301 | Introduction to Data Science | |
| STAT 4610 | Probability Theory | 3 |
| STAT 4620 | Statistical Theory | 3 |
| STAT 4366 | Statistical Communication, Collaboration, and Consulting | 5 |
| STAT 4460 | Senior Project: Statistics Capstone | 2 |
| Statistics Electives: | ||
| List A | ||
| Select from the following: | 9 | |
| Multilevel and Mixed Modeling | ||
| Bayesian Reasoning and Methods | ||
| Statistical Analysis of Time Series | ||
| Survival Analysis Methods | ||
| Categorical Data Analysis | ||
| Applied Multivariate Statistics | ||
| Generalized Linear Models | ||
| Applied Stochastic Processes | ||
| Advanced Design and Analysis of Experiments | ||
| Statistical Learning with R | ||
| List B | ||
| Select from the following: | 9 | |
Select any course from List A that was not taken to satisfy the requirement listed above | ||
| Teaching Statistics: Pedagogy, Content, Technology, and Assessment | ||
| Introduction to Statistical Computing with SAS and SQL | ||
| SAS Certification Preparation: Base Programming | ||
| SAS Certification Preparation: Advanced Programming | ||
| Introduction to Data Science | ||
| Data Visualization | ||
| Data Science Process and Ethics | ||
| Fundamentals of Machine Learning | ||
| Foundations and Applications of Deep Learning | ||
| Data Structures and Data Structures Laboratory | ||
| Algorithms and Complexity | ||
| Introduction to Database Management Systems | ||
| Transition to Advanced Mathematics | ||
| Differential Equations | ||
| Introduction to Mathematical Optimization | ||
| Combinatorics I | ||
| Graph Theory | ||
| Advanced Linear Algebra | ||
| Introduction to Numerical Analysis | ||
| Real Analysis I | ||
| Numerical Optimization | ||
| Game Theory | ||
| Lean Six Sigma Green Belt | ||
| SUPPORT COURSES | ||
| CSC 1001 & 1001L | Fundamentals of Computer Science and Fundamentals of Computer Science Laboratory | 4 |
| MATH 1151 | Linear Algebra | 3 |
| MATH/DATA 1264 | Calculus for Data Science I | 4 |
| MATH/DATA 1265 | Calculus for Data Science II | 4 |
| GENERAL EDUCATION (GE) | ||
| (See GE program requirements below) | 40 | |
| FREE ELECTIVES | ||
| Free Electives 2 | 5 | |
| Total Units | 120 | |
- 1
Required in Major or Support; also satisfies General Education (GE) requirement.
- 2
If a General Education (GE) course is used to satisfy a Major or Support requirement, additional units of Free Electives may be needed to complete the total units required for the degree.
General Education (GE) Requirements
- 43 units required, 3 of which are specified in Major and/or Support.
- If any of the remaining 40 Units is used to satisfy a Major or Support requirement, additional units of Free Electives may be needed to complete the total units required for the degree.
- See the complete GE course listing.
- A grade of C- or better is required in one course in each of the following GE Areas: 1A (English Composition), 1B (Critical Thinking), 1C (Oral Communication), and 2 (Mathematics and Quantitative Reasoning).
| Lower-Division General Education | ||
| Area 1 | English Communication and Critical Thinking | |
| 1A | Written Communication | 3 |
| 1B | Critical Thinking | 3 |
| 1C | Oral Communication | 3 |
| Area 2 | Mathematics and Quantitative Reasoning | |
| 2 | Mathematics and Quantitative Reasoning (3 units in Major) 1 | 0 |
| Area 3 | Arts and Humanities | |
| 3A | Arts | 3 |
| 3B | Humanities: Literature, Philosophy, Languages other than English | 3 |
| Area 4 | Social and Behavioral Sciences (Area 4 courses must come from at least two different course prefixes.) | |
| 4A | American Institutions (Title 5, Section 40404 Requirement) | 3 |
| 4B | Social and Behavioral Sciences | 3 |
| Area 5 | Physical and Life Sciences | |
| 5A | Physical Sciences | 3 |
| 5B | Life Sciences | 3 |
| 5C | Laboratory (may be embedded in a 5A or 5B course) | 1 |
| Area 6 | Ethnic Studies | |
| 6 | Ethnic Studies | 3 |
| Upper-Division General Education | ||
| Upper-Division 2/5 | Mathematics and Quantitative Reasoning or Physical and Life Sciences | 3 |
| Upper-Division 3 | Arts and Humanities | 3 |
| Upper-Division 4 | Social and Behavioral Sciences (Area 4 courses must come from at least two different course prefixes.) | 3 |
| Total Units | 40 | |
- 1
Required in Major or Support; also satisfies General Education (GE) requirement.