Statistics, Bachelor of Science College of Letters & Science

Office & Contact Information

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

The Program

Statistics majors may receive either a Bachelor of Arts (A.B.) or a Bachelor of Science (B.S.) degree. Both the A.B. and B.S. degree programs require coursework in both theoretical and applied statistics, highlighting the strong interdependence between statistical theory and its applications and computational aspects. The B.S. degree program has four tracks: Applied Statistics Track, General Track, Machine Learning Track, and the Statistical Data Science Track. Students choose one track to pursue based on their interests. Multiple track selection is not possible.

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 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.

The requirements for continuing students to change into the Statistics major can be found at Statistics Change of Major Requirements & Process.  

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.

The major requirements below are in addition to meeting University Degree Requirements & College Degree Requirements; unless otherwise noted. Respective of the Track, the minimum number of units required for the Statistics Bachelor of Science are 79, 83, 80, & 80.

Applied Statistics Track

Preparatory Subject Matter
Mathematics
MAT 021ACalculus (MAT 021A strongly preferred)4
or MAT 019A Calculus for Data-Driven Applications
or MAT 017A Calculus for Biology & Medicine
MAT 021BCalculus (MAT 021B strongly preferred)4
or MAT 019B Calculus for Data-Driven Applications
or MAT 017B Calculus for Biology & Medicine
MAT 021CCalculus (MAT 021C strongly preferred)4
or MAT 019C Calculus for Data-Driven Applications
or MAT 017C Calculus for Biology & Medicine
MAT 022ALinear Algebra4
or MAT 067 Modern Linear Algebra
or MAT 027A Linear Algebra with Applications to Biology
or BIS 027A Linear Algebra with Applications to Biology
Computer Science Engineering
ECS 032AIntroduction to Programming4
or ECS 032AV Introduction to Programming
or ECS 036A Programming & Problem Solving
Statistics
Choose one:4-8
STA 013
Elementary Statistics
or STA 013V
 Elementary Statistics
or STA 013Y
 Elementary Statistics
STA 013 or STA 013V or STA 013Y NOT recommended.
STA 032
Gateway to Statistical Data Science
STA 035A
& STA 035B
Statistical Data Science I
and Statistical Data Science II
STA 100
Applied Statistics for Biological Sciences
Domain Emphasis Prerequisites
Two introductory courses serving as the prerequisites to the chosen Domain Emphasis; see Domain Emphasis section, below. 7-8
Note: Additional coursework beyond this requirement may be needed to fulfill the Domain Emphasis prerequisites.
Preparatory Subject Matter Subtotal31-36
Depth Subject Matter
Core Coursework
Statistics24
STA 106
Applied Statistical Methods: Analysis of Variance
STA 108
Applied Statistical Methods: Regression Analysis
STA 130A
Mathematical Statistics: Brief Course
STA 130B
Mathematical Statistics: Brief Course
STA 138
Analysis of Categorical Data
STA 141A
Fundamentals of Statistical Data Science
Advanced Electives
Choose three: 12
STA 104
Applied Statistical Methods: Nonparametric Statistics
STA 135
Multivariate Data Analysis
STA 137
Applied Time Series Analysis
STA 141B
Data & Web Technologies for Data Analysis
Only one of STA 141B or STA 141C can be used as an elective.
STA 141C
Big Data & High Performance Statistical Computing
Only one of STA 141B or STA 141C can be used as an elective.
STA 144
Sampling Theory of Surveys
STA 145
Bayesian Statistical Inference
STA 160
Practice in Statistical Data Science
MAT 168
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.
STA 194HA
Special Studies for Honors Students
STA 194HB
Special Studies for Honors Students
STA 199
Special Study for Advanced Undergraduates
Domain Emphasis
Choose four upper division courses outside of statistics:12-16
A list of pre-approved elective courses can be found at:
Pre-Approved Applied AB Electives
Depth Subject Matter Subtotal48-52
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.
Total Units79-88

General Statistics Track

Preparatory Subject Matter
Mathematics
MAT 021ACalculus4
MAT 021BCalculus4
MAT 021CCalculus4
MAT 021DVector Analysis4
MAT 022ALinear Algebra4
or MAT 067 Modern Linear Algebra
or MAT 027A Linear Algebra with Applications to Biology
or BIS 027A Linear Algebra with Applications to Biology
Computer Science Engineering
ECS 032AIntroduction to Programming4
or ECS 032AV Introduction to Programming
or ECS 036A Programming & Problem Solving
Statistics
Choose one:4-8
STA 013
Elementary Statistics
or STA 013V
 Elementary Statistics
or STA 013Y
 Elementary Statistics
STA 013 or STA 013V or STA 013Y NOT recommended.
STA 032
Gateway to Statistical Data Science
STA 035A
& STA 035B
Statistical Data Science I
and Statistical Data Science II
STA 100
Applied Statistics for Biological Sciences
Preparatory Subject Matter Subtotal28-32
Depth Subject Matter
Core Coursework
Statistics24
STA 106
Applied Statistical Methods: Analysis of Variance
STA 108
Applied Statistical Methods: Regression Analysis
STA 131A
Introduction to Probability Theory
STA 131B
Introduction to Mathematical Statistics
STA 131C
Introduction to Mathematical Statistics
STA 138
Analysis of Categorical Data
Mathematics16
MAT 108
Introduction to Abstract Mathematics
or MAT 108V
 Introduction to Abstract Mathematics
or MAT 127C
 Real Analysis
MAT 127A
Real Analysis
MAT 127B
Real Analysis
MAT 167
Applied Linear Algebra
Advanced Electives
Choose three:12
STA 104
Applied Statistical Methods: Nonparametric Statistics
STA 135
Multivariate Data Analysis
STA 137
Applied Time Series Analysis
STA 141A
Fundamentals of Statistical Data Science
STA 141B
Data & Web Technologies for Data Analysis
Only one of STA 141B or STA 141C can be used as an elective.
STA 141C
Big Data & High Performance Statistical Computing
Only one of STA 141B or STA 141C can be used as an elective.
STA 142A
Statistical Learning I
STA 142B
Statistical Learning II
STA 144
Sampling Theory of Surveys
STA 145
Bayesian Statistical Inference
STA 160
Practice in Statistical Data Science
MAT 168
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.
STA 194HA
Special Studies for Honors Students
STA 194HB
Special Studies for Honors Students
STA 199
Special Study for Advanced Undergraduates
Related Elective Course3-4
One upper division course approved by faculty advisor. A list of pre-approved electives can be found at:
Pre-Approved Electives List
Depth Subject Matter Subtotal55-56
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.
Total Units83-88

Machine Learning Track

Preparatory Subject Matter
Mathematics
MAT 021ACalculus4
MAT 021BCalculus4
MAT 021CCalculus4
MAT 021DVector Analysis4
MAT 022ALinear Algebra4
or MAT 067 Modern Linear Algebra
or MAT 027A Linear Algebra with Applications to Biology
or BIS 027A Linear Algebra with Applications to Biology
Computer Science Engineering
ECS 032AIntroduction to Programming4
or ECS 032AV Introduction to Programming
or ECS 036A Programming & Problem Solving
Note: Additional coursework in Python is strongly recommended; e.g., ECS 032B.
Statistics
Choose one:4-8
STA 013
Elementary Statistics
or STA 013V
 Elementary Statistics
or STA 013Y
 Elementary Statistics
STA 013 or STA 013V or STA 013Y NOT recommended.
STA 032
Gateway to Statistical Data Science
STA 035A
& STA 035B
Statistical Data Science I
and Statistical Data Science II
STA 100
Applied Statistics for Biological Sciences
Preparatory Subject Matter Subtotal28-32
Depth Subject Matter
Core Coursework
Statistics36
STA 106
Applied Statistical Methods: Analysis of Variance
STA 108
Applied Statistical Methods: Regression Analysis
STA 131A
Introduction to Probability Theory
STA 131B
Introduction to Mathematical Statistics
STA 131C
Introduction to Mathematical Statistics
STA 141A
Fundamentals of Statistical Data Science
STA 142A
Statistical Learning I
STA 142B
Statistical Learning II
STA 144
Sampling Theory of Surveys
or STA 145
 Bayesian Statistical Inference
Mathematics4
MAT 167
Applied Linear Algebra
or MAT 168
 Optimization
Advanced Electives
Choose three:12
STA 104
Applied Statistical Methods: Nonparametric Statistics
STA 135
Multivariate Data Analysis
STA 137
Applied Time Series Analysis
STA 138
Analysis of Categorical Data
STA 141B
Data & Web Technologies for Data Analysis
STA 141C
Big Data & High Performance Statistical Computing
STA 144
Sampling Theory of Surveys
STA 145
Bayesian Statistical Inference
MAT 127A
Real Analysis
MAT 128A
Numerical Analysis
MAT 170
Mathematics for Data Analytics & Decision Making
ECS 119
Data Processing Pipelines
ECS 122A
Algorithm Design & Analysis
or ECS 117
 Algorithms for Data Science
ECS 158
Programming on Parallel Architectures
ECS 163
Information Visualization
ECS 165A
Database Systems
or ECS 116
 Databases for Non-Majors
ECS 170
Introduction to Artificial Intelligence
ECS 174
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.
STA 194HA
Special Studies for Honors Students
STA 194HB
Special Studies for Honors Students
STA 199
Special Study for Advanced Undergraduates
Note: A course used to fulfill a core requirement cannot be used as an elective.
Depth Subject Matter Subtotal52
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.
Total Units80-84

Statistical Data Science Track

Preparatory Subject Matter
Mathematics
MAT 021ACalculus4
MAT 021BCalculus4
MAT 021CCalculus4
MAT 021DVector Analysis4
MAT 022ALinear Algebra4
or MAT 067 Modern Linear Algebra
or MAT 027A Linear Algebra with Applications to Biology
or BIS 027A Linear Algebra with Applications to Biology
Computer Science Engineering
ECS 032AIntroduction to Programming4
or ECS 032AV Introduction to Programming
or ECS 036A Programming & Problem Solving
Note: Additional coursework in Python is strongly recommended; e.g., ECS 032B.
Statistics
Choose one:4-8
STA 013
Elementary Statistics
or STA 013V
 Elementary Statistics
or STA 013Y
 Elementary Statistics
STA 013 or STA 013V or STA 013Y NOT recommended.
STA 032
Gateway to Statistical Data Science
STA 035A
& STA 035B
Statistical Data Science I
and Statistical Data Science II
STA 100
Applied Statistics for Biological Sciences
Preparatory Subject Matter Subtotal28-32
Depth Subject Matter
Core Coursework
Statistics36
STA 106
Applied Statistical Methods: Analysis of Variance
STA 108
Applied Statistical Methods: Regression Analysis
STA 131A
Introduction to Probability Theory
or STA 130A
 Mathematical Statistics: Brief Course
STA 131B
Introduction to Mathematical Statistics
or STA 130B
 Mathematical Statistics: Brief Course
STA 135
Multivariate Data Analysis
STA 141A
Fundamentals of Statistical Data Science
STA 141B
Data & Web Technologies for Data Analysis
STA 141C
Big Data & High Performance Statistical Computing
STA 160
Practice in Statistical Data Science
Machine Learning4
STA 142A
Statistical Learning I
or STA 142B
 Statistical Learning II
or ECS 111
 Applied Machine Learning for Non-Majors
or ECS 171
 Machine Learning
Mathematics4
MAT 167
Applied Linear Algebra
or MAT 168
 Optimization
Advanced Electives
Choose two:8
STA 104
Applied Statistical Methods: 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 & Decision Making
ECS 119
Data Processing Pipelines
ECS 122A
Algorithm Design & Analysis
or ECS 117
 Algorithms for Data Science
ECS 158
Programming on Parallel Architectures
ECS 163
Information Visualization
ECS 165A
Database Systems
or ECS 116
 Databases for Non-Majors
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.
STA 194HA
Special Studies for Honors Students
STA 194HB
Special Studies for Honors Students
STA 199
Special Study for Advanced Undergraduates
Note: A course used to fulfill a core requirement cannot be used as an advanced elective.
Depth Subject Matter Subtotal52
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.
Total Units80-84

Sample academic plans can be found on the Department of Statistics website; see below. These plans 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.  

Sample Academic Plans