2024-2025 Academic Catalog
Welcome to Virginia Tech! We are excited that you are here planning your time as a Hokie.
Welcome to Virginia Tech! We are excited that you are here planning your time as a Hokie.
| Code | Title | Credits |
|---|---|---|
| Degree Core Requirements | ||
| STAT 3006 | Statistical Methods | 3 |
| STAT 3104 | Probability and Distributions | 3 |
| STAT 4105 | Theoretical Statistics | 3 |
| STAT 4106 | Theoretical Statistics | 3 |
| STAT 4204 | Experimental Designs | 3 |
| STAT 4214 | Methods of Regression Analysis | 3 |
| STAT 4444 | Applied Bayesian Statistics | 3 |
| Subtotal | 21 | |
| ||
| Major Requirements | ||
| STAT/CMDA/CS 3654 | Introductory Data Analytics and Visualization | 3 |
| STAT 4004 | Methods of Statistical Computing | 3 |
| STAT 4024 | Communication in Statistical Collaborations | 3 |
| MATH 2204 | Introduction to Multivariable Calculus | 3 |
| MATH 2114 | Introduction to Linear Algebra | 3 |
| ||
| Computer Programming Required Courses. Select one of the following: | 3 | |
| Introduction to Programming in Python | ||
| Introduction to Software Design | ||
| Subtotal | 18 | |
| Option Required Courses | ||
| STAT 4584 | Advanced Calculus for Statistics | 3 |
| or MATH 3224 | Advanced Calculus | |
| MATH 3034 | Introduction to Proofs | 3 |
| Computer Programming Required Courses. Select one of the following: | 3 | |
| Introduction to Computational Thinking | ||
| Introduction to Programming in Python | ||
| Introduction to Software Design | ||
| Intermediate Programming in Python | ||
| Software Design and Data Structures | ||
| SAS Programming | ||
| ||
| Restricted Electives | ||
| Select four of the following (at least two must be STAT) | 12 | |
| Data Visualization | ||
| Introduction to Sports Analytics Research | ||
| Nonparametric Statistics | ||
| Sports Analytics Statistical Research | ||
| Introduction to Statistical Genomics | ||
| Applied Multivariate Analysis | ||
| Introduction to Categorical Data Analysis | ||
| Sample Survey Methods | ||
| Applied Statistical Time Series Analysis | ||
| Intermediate Data Analytics and Machine Learning | ||
| Computational Intensive Stochastic Modleing | ||
| Deep Learning | ||
| Elementary Econometrics 1 | ||
| Field Study 2 | ||
or STAT 4994 | Undergraduate Research | |
| Parallel Computation 3 | ||
| Machine Learning 3 | ||
| Applied Combinatorics and Graph Theory 3 | ||
| Linear Algebra II 3 | ||
| Applied Mathematical Modeling 3 | ||
| Elementary Real Analysis 3 | ||
| Statistical Quality Control 3 | ||
| Subtotal | 21 | |
| Free Electives | ||
| Select remaining credits required for the degree: | 13 | |
| Subtotal | 13 | |
| Pathways to General Education | ||
| Pathways Concept 1 - Discourse | ||
| ENGL 1105 | First-Year Writing (1F) | 3 |
| ENGL 1106 | First-Year Writing (1F) | 3 |
| ENGL 3764 | Technical Writing (1A) | 3 |
| Pathways Concept 2 - Critical Thinking in the Humanities | ||
| Select six credits in Pathway 2 | 6 | |
| Pathways Concept 3 - Reasoning in the Social Sciences | ||
| Select six credits in Pathway 3 | 6 | |
| Pathways Concept 4 - Reasoning in the Natural Sciences | ||
| Select six credits in Pathway 4 | 6 | |
| To fulfill the Pathways Concept 4: Reasoning in the Natural Sciences requirements, only BIOL, CHEM, GEOS, ISC, NEUR, PHYS, and PSYC courses approved for Pathways Concept 4 may be selected. | ||
| Pathways Concept 5 - Quantitative and Computational Thinking | ||
| MATH 1225 & MATH 1226 | Calculus of a Single Variable and Calculus of a Single Variable (required of all students majoring in Statistics; 5F) | 8 |
| STAT 3005 | Statistical Methods (required of all students majoring in Statistics; 5F) | 3 |
| Pathways Concept 6 - Critique and Practice in Design and the Arts | ||
| Select 6 credits = 3 in design + 3 in arts, or 6 in integrated design and arts) | 6 | |
| Pathways Concept 7 - Critical Analysis of Identity and Equity in the United States | ||
| Select three credits in Pathway 7 | 3 | |
| Subtotal | 47 | |
| Total Credits | 120 | |
For Economic majors or minors, ECON 4304 Introduction to Econometric Methods, can substitute for STAT 4804.
A maximum of 3 credits from either STAT 4964 (for an internship or other summer experience), or STAT 4994, may count as a Statistics elective with prior approval from the department.
An upper-level course that is not offered by the Department of Statistics. Be aware of all prerequisites.
| Code | Title | Credits |
|---|---|---|
| Degree Core Requirements | ||
| STAT 3006 | Statistical Methods | 3 |
| STAT 3104 | Probability and Distributions | 3 |
| STAT 4105 | Theoretical Statistics | 3 |
| STAT 4106 | Theoretical Statistics | 3 |
| STAT 4204 | Experimental Designs | 3 |
| STAT 4214 | Methods of Regression Analysis | 3 |
| STAT 4444 | Applied Bayesian Statistics | 3 |
| Subtotal | 21 | |
| Major Requirements | ||
| STAT 3654 | Introductory Data Analytics and Visualization | 3 |
| STAT 4004 | Methods of Statistical Computing | 3 |
| STAT 4024 | Communication in Statistical Collaborations | 3 |
| MATH 2204 | Introduction to Multivariable Calculus | 3 |
| MATH 2114 | Introduction to Linear Algebra | 3 |
| Select one of the following: | 3 | |
| Introduction to Programming in Python | ||
| Introduction to Software Design | ||
| Subtotal | 18 | |
| Option Required Courses | ||
| STAT 4584 | Advanced Calculus for Statistics | 3 |
| or MATH 3224 | Advanced Calculus | |
| MATH 3034 | Introduction to Proofs | 3 |
| Select one of the following: 4 | 3 | |
| Introduction to Computational Thinking | ||
| Introduction to Programming in Python 1 | ||
| Introduction to Software Design | ||
| Intermediate Programming in Python | ||
| Software Design and Data Structures | ||
MATH 3054 | 4 | |
| SAS Programming | ||
| Restricted Electives | ||
| Select four of the following (at least two must be STAT) | 12 | |
| Data Visualization | ||
| Nonparametric Statistics | ||
| Introduction to Statistical Genomics | ||
| Applied Multivariate Analysis | ||
| Introduction to Categorical Data Analysis | ||
| Sample Survey Methods | ||
| Applied Statistical Time Series Analysis | ||
| Intermediate Data Analytics and Machine Learning | ||
| Computational Intensive Stochastic Modleing | ||
| Elementary Econometrics 1 | ||
| Field Study 2 | ||
or STAT 4994 | Undergraduate Research | |
| Parallel Computation 3 | ||
| Machine Learning 3 | ||
| Applied Combinatorics and Graph Theory 3 | ||
| Linear Algebra II 3 | ||
| Applied Mathematical Modeling 3 | ||
| Elementary Real Analysis 3 | ||
| Statistical Quality Control 3 | ||
| Subtotal | 21 | |
| Free Electives | ||
| Select remaining credits required for the degree: | 13 | |
| Subtotal | 13 | |
| Pathways to General Education | ||
| Pathways Concept 1 - Discourse | ||
| ENGL 1105 | First-Year Writing (1F) | 3 |
| ENGL 1106 | First-Year Writing (1F) | 3 |
| ENGL 3764 | Technical Writing (1F) | 3 |
| Pathways Concept 2 - Critical Thinking in the Humanities | ||
| Select six credits in Pathway 2 | 6 | |
| Pathways Concept 3 - Reasoning in the Social Sciences | ||
| Select six credits in Pathway 3 | 6 | |
| Pathways Concept 4 - Reasoning in the Natural Sciences | ||
| Select six credits in Pathway 4 | 6 | |
| Pathways Concept 5 - Quantitative and Computational Thinking | ||
| MATH 1225 & MATH 1226 | Calculus of a Single Variable and Calculus of a Single Variable (required of all students majoring in Statistics; 5F) | 8 |
| STAT 3005 | Statistical Methods (required of all students majoring in Statistics; 5F) | 3 |
| Pathways Concept 6 - Critique and Practice in Design and the Arts | ||
| Select 6 credits = 3 in design + 3 in arts, or 6 in integrated design and arts) | 6 | |
| Pathways Concept 7 - Critical Analysis of Identity and Equity in the United States | ||
| Select three credits in Pathway 7 | 3 | |
| Subtotal | 47 | |
| Total Credits | 120 | |
For Economic majors or minors, ECON 4304 Introduction to Econometric Methods can substitute for STAT 4804 Elementary Econometrics.
A maximum of 3 credits from either STAT 4964 Field Study (for internships or other summer experience), or STAT 4994 Undergraduate Research may count as a Statistic elective with prior approval from the department.
An upper-level course that is not offered by the Department of Statistics. Be aware of all prerequisites.
These courses must be different from the course completed in the major requirements section.
Satisfactory Progress Towards Degree and Minimum Grade Requirements
Virginia Tech requires 120 credit hours to graduate with a GPA of 2.0 or greater for all hours attempted. The 120 credit hours must include all required courses for the statistics major as outlined in this check-sheet. Within the first two attempts, including attempts ending in course withdrawal, students must earn a C- or better in all MATH, STAT, or CS designated courses for the degree (or equivalents thereof). In addition, students must have an in-major GPA of 2.0 or greater. All STAT courses, any course taken to fulfill Statistical Methods and Theory option elective credit, and all required MATH and CS courses will be used to calculate in-major GPA. If 120 credit hours are reached and a student does not meet the GPA requirement, the student must take additional STAT courses to raise the in-major GPA to a 2.0.
Some courses listed on this checksheet may have prerequisites; please consult the Undergraduate Course Catalog or check with your advisor for more information.
CMDA 2005 Integrated Quantitative Sciences-CMDA 2006 Integrated Quantitative Sciences is equivalent to all the following: STAT 3005 Statistical Methods and STAT 3006 Statistical Methods and STAT 3104 Probability and Distributions and (MATH 2214 Introduction to Differential Equations OR MATH 2214H Introduction to Differential Equations)and (MATH 2204 Introduction to Multivariable Calculus or MATH 2204H Introduction to Multivariable Calculus)
Students who did not successfully complete at least two years of a single foreign, classical, or sign language during high school must successfully complete six semester hours of a single foreign, classical, or sign language at the college level. Courses taken to meet this requirement do not count toward the hours required for graduation. Please consult the Undergraduate Catalog for details.
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