This track emphasizes data handling skills and statistical computation. It is recommended for students interested in statistical learning methodology, advanced data handling techniques and computational aspects of statistical analysis.
Notes:
These requirements were put into effect Fall 2020. Requirements from previous years can be found in the General Catalog Archive.
Preparatory Subject Matter (28-32 units)
Mathematics (20 units)
- MAT 21A Calculus
- MAT 21B Calculus
- MAT 21C Calculus
- MAT 21D Vector Analysis
- MAT 22A Linear Algebra
- or MAT 67 Modern Linear Algebra
- or MAT/BIS 27A Linear Algebra with Applications to Biology
Computer Science (4 units)
- ECS 32A Intro to Programming
Statistics (4-8 units)
- STA 32 Gateway to Statistical Data Science
Depth Subject Matter (52 units)
Core Coursework
Statistics (36 units)
- STA 106 Analysis of Variance
- STA 108 Regression Analysis
- STA 131A Intro to Probability Theory
- or STA 130A Mathematical Statistics: Brief Course
- STA 131B Intro to Mathematical Statistics
- or STA 130B Mathematical Statistics: Brief Course
- STA 141A Fundamentals of Statistical Data Science
- STA 141B Data and Web Technologies for Data Analysis
- STA 141C Big Data and High Performance Statistical Computing
- STA 135 Multivariate Data Analysis
- STA 160 Practice in Statistical Data Science
Machine Learning (4 units)
- STA 142A Statistical Learning I
Mathematics (4 units)
Advanced Electives (8 units)
Choose two:
- STA 104 Nonparametric Statistics
- STA 137 Applied time Series Analysis
- STA 138 Analysis of Categorical Data
- STA 142A Statistical Learning I
- STA 142B Statistical Learning II
- STA 144 Sampling Theory of Surveys
- STA 145 Bayesian Statistical Inference
- MAT 128A Numerical Analysis
- MAT 170 Mathematics for Data Analytics and Decision Making
- ECS 116 Databases for Non-Majors
- or ECS 165A Database Systems
- ECS 117 Algorithms for Data Science
- or ECS 122A Algorithm Design and Analysis
- ECS 119 Data Processing Pipelines
- ECS 158 Programming and Parallel Architectures
- ECS 163 Information Visualization
- One approved course of 4 units from STA 199, 194HA, or 194HB may be used.
Note: A course used to fulfill a core requirement cannot be used as a restricted elective.
Total Units: 80-84
Major GPA Requirements
- Minimum 2.0 GPA in UC Davis courses used in the major.
- Minimum 2.0 GPA in Upper Division UC Davis courses used in the major.
Statistics-Statistical Data Science Track Sample Academic Plan
This schedule can be used as a guide, but students are recommended to meet with an advisor on a regular basis to make a customized plan that works best for their unique needs and priorities. Course offerings may also change year to year so please be sure to utilize the Academic Planning Resources provided.
Academic Planning Resources:
- Statistics Course Offerings Schedule
- Computer Science Course Offerings Schedule
- Mathematics Course Offerings Schedule
| First-year | Fall | Winter | Spring |
| MAT 21A | MAT 21B | MAT 21C | |
| ECS 32A or 36A | STA 13 or 32 or 35B* or 100 | ||
| Second-year | Fall | Winter | Spring |
| MAT 21D | STA 108 | STA 106 | |
| MAT 22A or 27A or 67 | ECS 32B** | STA 141A | |
| Third-year | Fall | Winter | Spring |
| STA 131A or 130A | STA 131B or 130B | STA 141C | |
| MAT 167 or 168 | STA 141B | STA 135 | |
| Fourth-year | Fall | Winter | Spring |
| STA/MAT/ECS Advanced Elective | STA 142A or STA 142B or ECS 111 or ECS 171 | STA 160 | |
| STA/MAT/ECS Advanced Elective |
* STA 35A must be taken prior to STA 35A.
** Recommended course (not required).