Statistics, Bachelor of Science College of Letters & Science

The Major Program

Statistics enables us to make inferences about entire populations, based on samples extracted from those populations. Statistical methods can be applied to problems from almost every discipline and they are vitally important to researchers in agricultural, biological, environmental, social, engineering, and medical sciences.

The Program

Statistics majors may receive either a Bachelor of Arts or a Bachelor of Science degree. Both the A.B. and the B.S. programs require theoretical and applied course work and underscore the strong interdependence of statistical theory and the applications and computational aspects of statistics. The B.S. degree program has five tracks: Applied Statistics Track, Computational Statistics Track, General Track, Machine Learning Track, and the Statistical Data Science Track.

B.S. in Statistics-Applied Statistics Track emphasizes statistical applications. This track is recommended for students who are interested in applications of statistical techniques to various disciplines including the biological, physical and social sciences.

B.S. in Statistic-Computational Statistics Track emphasizes computing. This track is recommended for students interested in the computational and data management aspects of statistical analysis.

B.S. in Statistics-General Track emphasizes statistical theory and is especially recommended as preparation for graduate study in statistics.

B.S in Statistics-Machine Learning Track emphasizes algorithmic and theoretical aspects of statistical learning methodologies that are geared towards building predictive and explanatory models for large and complex data. It is recommended for students interested in pursuing graduate programs in statistics, machine learning, or data science, as well as for students interested in learning statistical techniques for industry.

B.S. in Statistic-Statistical Data Science Track emphasizes data handling skills and statistical computation. This track is recommended for students interested in statistical learning methodology, advanced data handling techniques and computational aspects of statistical analysis.

Major Advisors

For a current list of faculty and staff advisors, see Undergraduate Advising.

Students are encouraged to meet with an advisor to plan a program as early as possible.

Career Alternatives

Probability models, statistical methods, and computational techniques are used in a great many fields, including the biological, physical, social, and health sciences, business, and engineering. The wide applicability of statistics is reflected in the strong demand for graduates with statistical training in both the public and private sectors. Employment opportunities include careers in data & policy analysis in government & industry, financial management, quality control, insurance & healthcare industry, actuarial science, engineering, public health, biological & pharmaceutical research, law, and education. Students with an undergraduate degree in statistics have entered advanced studies in statistics, economics, finance, psychology, medicine, business management & analytics, and other professional school programs.

Applied Statistics Track

Preparatory Subject Matter
Mathematics
Choose a series:9-12
Short Calculus
and Short Calculus
and Short Calculus
Calculus for Biology & Medicine
and Calculus for Biology & Medicine
and Calculus for Biology & Medicine
Calculus
and Calculus
and Calculus
MAT 021 series preferred.
MAT 022ALinear Algebra3
Computer Science Engineering
ECS 032AIntroduction to Programming4
or ECS 036A Programming & Problem Solving
Statistics
Choose one:4
Elementary Statistics
Elementary Statistics
Gateway to Statistical Data Science
Applied Statistics for Biological Sciences
STA 032 or STA 100 preferred.
Cluster Elective Prerequisites
Two introductory courses serving as the prerequisites to the chosen Cluster Electives (see Cluster Electives section below). 7-8
Note: Additional coursework beyond this requirement may be needed to fulfill the Cluster Elective prerequisites.
Preparatory Subject Matter Subtotal27-31
Depth Subject Matter
Core Coursework
Statistics24
Applied Statistical Methods: Analysis of Variance
Applied Statistical Methods: Regression Analysis
Mathematical Statistics: Brief Course
Mathematical Statistics: Brief Course
Analysis of Categorical Data
Fundamentals of Statistical Data Science
Restricted Electives
Choose three: 12
Applied Statistical Methods: Nonparametric Statistics
Multivariate Data Analysis
Applied Time Series Analysis
Data & Web Technologies for Data Analysis
Only one of STA 141B or STA 141C can be used as an elective.
Big Data & High Performance Statistical Computing
Only one of STA 141B or STA 141C can be used as an elective.
Sampling Theory of Surveys
Bayesian Statistical Inference
Practice in Statistical Data Science
Optimization
With advisor approval, one of STA 194HA or STA 194HB or STA 199 may be used as an elective. The course must be taken for four units.
Special Studies for Honors Students
Special Studies for Honors Students
Special Study for Advanced Undergraduates
Cluster Electives
Choose four upper division elective courses outside of statistics:12-16
Cluster electives are chosen with and must be approved by the major advisor. A list of pre-approved electives can be found on the Statistics Department website. Electives must follow a coherent sequence in one single disciple/cluster where statistical methods and models are applied. At least three of the cluster electives must cover the quantitative aspects of the discipline.
Depth Subject Matter Subtotal48-52
Total Units75-83

Computational Statistics Track

Preparatory Subject Matter
Mathematics
MAT 021ACalculus4
MAT 021BCalculus4
MAT 021CCalculus4
MAT 021DVector Analysis4
MAT 022ALinear Algebra3
Computer Science Engineering
Choose one:4-5
Software Development in UNIX & C++
Data Structures, Algorithms, & Programming
Or the equivalent.
Statistics
Choose one:4
Elementary Statistics
Elementary Statistics
Gateway to Statistical Data Science
Applied Statistics for Biological Sciences
STA 032 or STA 100 preferred.
Preparatory Subject Matter Subtotal27-28
Depth Subject Matter
Statistics
STA 106Applied Statistical Methods: Analysis of Variance4
STA 108Applied Statistical Methods: Regression Analysis4
STA 131AIntroduction to Probability Theory4
STA 131BIntroduction to Mathematical Statistics4
STA 141AFundamentals of Statistical Data Science4
Choose two:8
Applied Statistical Methods: Nonparametric Statistics
Multivariate Data Analysis
Applied Time Series Analysis
Analysis of Categorical Data
Statistical Learning I
Statistical Learning II
Sampling Theory of Surveys
Bayesian Statistical Inference
Practice in Statistical Data Science
With advisor approval, one of STA 194HA or STA 194HB or STA 199 may be used as an elective. The course must be taken for four units.
Special Studies for Honors Students
Special Studies for Honors Students
Special Study for Advanced Undergraduates
Programming, Data Management & Data Tehnologies
ECS 130Scientific Computation4
or ECS 145 Scripting Languages & Their Applications
ECS 165ADatabase Systems4
Scientific Computational Algorithm & Visualization
Choose two:8
Algorithm Design & Analysis
Computational Structural Bioinformatics
Programming Languages
Programming on Parallel Architectures
Information Interfaces
Data & Web Technologies for Data Analysis
Big Data & High Performance Statistical Computing
Mathematics
Choose two:8
Mathematical Biology
Numerical Analysis
Numerical Analysis in Solution of Equations
Fourier Analysis
Combinatorics
Discrete Mathematics
Mathematics for Data Analytics & Decision Making
Mathematics & Computers
Applied Linear Algebra
Optimization
Depth Subject Matter Subtotal52
Total Units79-80

General Statistics Track

Preparatory Subject Matter
Mathematics
MAT 021ACalculus4
MAT 021BCalculus4
MAT 021CCalculus4
MAT 021DVector Analysis4
MAT 022ALinear Algebra3-4
or MAT 067 Modern Linear Algebra
Computer Science Engineering
ECS 032AIntroduction to Programming4
or ECS 036A Programming & Problem Solving
Statistics
Choose one:4
Elementary Statistics
Elementary Statistics
Gateway to Statistical Data Science
Applied Statistics for Biological Sciences
STA 032 or STA 100 preferred.
Preparatory Subject Matter Subtotal27-28
Depth Subject Matter
Core Coursework
Statistics24
Applied Statistical Methods: Analysis of Variance
Applied Statistical Methods: Regression Analysis
Introduction to Probability Theory
Introduction to Mathematical Statistics
Introduction to Mathematical Statistics
Analysis of Categorical Data
Mathematics16
Introduction to Abstract Mathematics
Real Analysis
Real Analysis
Real Analysis
Applied Linear Algebra
Restricted Electives
Choose three:12
Applied Statistical Methods: Nonparametric Statistics
Multivariate Data Analysis
Applied Time Series Analysis
Fundamentals of Statistical Data Science
Data & Web Technologies for Data Analysis
Only one of STA 141B or STA 141C can be used as an elective.
Big Data & High Performance Statistical Computing
Only one of STA 141B or STA 141C can be used as an elective.
Statistical Learning I
Statistical Learning II
Sampling Theory of Surveys
Bayesian Statistical Inference
Practice in Statistical Data Science
Optimization
With advisor approval, one of STA 194HA or STA 194HB or STA 199 may be used as an elective. The course must be taken for four units.
Special Studies for Honors Students
Special Studies for Honors Students
Special Study for Advanced Undergraduates
Related Elective Course
One upper division course outside of Statistics approved by major advisor. A list of pre-approved electives can be found on the Statistics Department website. The Related Elective should be in mathematics, computer science or cover quantitative aspects of a substantive discipline. 3-4
Depth Subject Matter Subtotal55-56
Total Units82-84

Machine Learning Track

Preparatory Subject Matter
Mathematics
MAT 021ACalculus4
MAT 021BCalculus4
MAT 021CCalculus4
MAT 021DVector Analysis4
MAT 022ALinear Algebra3
Computer Science Engineering
ECS 032AIntroduction to Programming4
or ECS 036A Programming & Problem Solving
Note: Additional coursework in Python is strongly recommended; e.g., ECS 032B.
Statistics
Choose one:4
Elementary Statistics
Elementary Statistics
Gateway to Statistical Data Science
Applied Statistics for Biological Sciences
STA 032 or STA 100 preferred.
Preparatory Subject Matter Subtotal27
Depth Subject Matter
Core Coursework
Statistics36
Applied Statistical Methods: Analysis of Variance
Applied Statistical Methods: Regression Analysis
Introduction to Probability Theory
Introduction to Mathematical Statistics
Introduction to Mathematical Statistics
Fundamentals of Statistical Data Science
Statistical Learning I
Statistical Learning II
Sampling Theory of Surveys
Bayesian Statistical Inference
Mathematics4
Applied Linear Algebra
Optimization
Restricted Electives
Choose three:12
Applied Statistical Methods: Nonparametric Statistics
Multivariate Data Analysis
Applied Time Series Analysis
Analysis of Categorical Data
Data & Web Technologies for Data Analysis
Big Data & High Performance Statistical Computing
Sampling Theory of Surveys
Bayesian Statistical Inference
Real Analysis
Numerical Analysis
Mathematics for Data Analytics & Decision Making
Algorithm Design & Analysis
Programming on Parallel Architectures
Information Interfaces
Software Engineering
Introduction to Artificial Intelligence
Computer Vision
With advisor approval, one of STA 194HA or STA 194HB or STA 199 may be used as an elective. The course must be taken for four units.
Special Studies for Honors Students
Special Studies for Honors Students
Special Study for Advanced Undergraduates
Note: A course used to fulfill the core requirement cannot be used as an elective.
Depth Subject Matter Subtotal52
Total Units79

Statistical Data Science Track

Preparatory Subject Matter
Mathematics
MAT 021ACalculus4
MAT 021BCalculus4
MAT 021CCalculus4
MAT 021DVector Analysis4
MAT 022ALinear Algebra3
Computer Science Engineering
ECS 032AIntroduction to Programming4
or ECS 036A Programming & Problem Solving
Note: Additional coursework in Python is strongly recommended; e.g., ECS 032B.
Statistics
Choose one:4
Elementary Statistics
Elementary Statistics
Gateway to Statistical Data Science
Applied Statistics for Biological Sciences
STA 032 or STA 100 preferred.
Preparatory Subject Matter Subtotal27
Depth Subject Matter
Core Coursework
Statistics36
Applied Statistical Methods: Analysis of Variance
Applied Statistical Methods: Regression Analysis
Introduction to Probability Theory
Mathematical Statistics: Brief Course
Introduction to Mathematical Statistics
Mathematical Statistics: Brief Course
Multivariate Data Analysis
Fundamentals of Statistical Data Science
Data & Web Technologies for Data Analysis
Big Data & High Performance Statistical Computing
Practice in Statistical Data Science
Machine Learning4
Statistical Learning I
Machine Learning
Mathematics4
Applied Linear Algebra
Optimization
Restricted Electives
Choose two:8
Applied Statistical Methods: Nonparametric Statistics
Applied Time Series Analysis
Analysis of Categorical Data
Statistical Learning I
Statistical Learning II
Sampling Theory of Surveys
Bayesian Statistical Inference
Numerical Analysis
Mathematics for Data Analytics & Decision Making
Algorithm Design & Analysis
Programming on Parallel Architectures
Information Interfaces
Database Systems
With advisor approval, one of STA 194HA or STA 194HB or STA 199 may be used as an elective. The course must be taken for four units.
Special Studies for Honors Students
Special Studies for Honors Students
Special Study for Advanced Undergraduates
Note: A course used to fulfill a core requirement cannot be used as a restricted elective.
Depth Subject Matter Subtotal52
Total Units79