Statistics B.S.

A Bachelor of Science degree with a major in Statistics requires the completion of the Elon Core Curriculum as well as the Major Requirements listed below.

Major Requirements

Statistical foundations: 12 sh

STS 2120Statistics in Application

4 sh

STS 2300Introduction to Data Analytics

4 sh

STS 2320Statistical Modeling

4 sh

STS 0070Senior Comprehensive Evaluation

0

Study design and analysis: 4 sh

Select one study design and analysis course from the following:

STS 3230Methods in Survey Design, Sampling & Estimation

4 sh

STS 3250Design and Analysis of Experiments

4 sh

Statistical computing: 4 sh

Select one statistical computing course from the following

STS 3270Statistical Computing for Data Management

4 sh

STS 3300Statistical Methods for Data Analytics

4 sh

Statistical theory: 4 sh

Select one statistical theory course from the following

STS 3410/MTH 3410Probability Theory and Statistics

4 sh

STS 3470Statistical Computing for Simulation and Theory

4 sh

Note: students in the Actuarial Science concentration are required to take /sts-3410'>STS 3410.

Statistics electives: 4 sh

Select at least one course from the following:

STS 3230Methods in Survey Design, Sampling & Estimation

4 sh

STS 2560Applied Nonparametric Statistics

4 sh

STS 3250Design and Analysis of Experiments

4 sh

STS 3270Statistical Computing for Data Management

4 sh

STS 3300Statistical Methods for Data Analytics

4 sh

STS 3410/MTH 3410Probability Theory and Statistics

4 sh

STS 3470Statistical Computing for Simulation and Theory

4 sh

The same course cannot count both as a study design and analysis, statistical computing, or statistical theory requirement and as an elective.

Mathematical foundations: 8 sh

MTH 1510Calculus I

4 sh

MTH 2510Calculus II

4 sh

Capstone: 4 sh

A related experiential/capstone experience approved by the department (4 sh). Approved options include:

STS 4980Statistics Practicum

4 sh

STS 4985Internship in Statistics

2-4 sh

STS 4999Independent Research in Statistics

2-4 sh

Total Credit Hours: 40

Concentrations

Select one of the following concentrations:

Mathematical statistics: 16 sh

Required courses: 12 sh

MTH 2310Linear Algebra

4 sh

MTH 2520Multivariable Calculus and Analytic Geometry

4 sh

MTH 3300Mathematical Reasoning

4 sh

Select one course from the following that was not already taken as part of the major requirements: 4 sh

STS 3410/MTH 3410Probability Theory and Statistics

4 sh

STS 3470Statistical Computing for Simulation and Theory

4 sh

Actuarial Science: 20 sh

Required course: 16 sh

ECO 1000Principles of Economics

4 sh

ACC 2010Principles of Accounting

4 sh

BUS 2110Management Information Systems

4 sh

FIN 3430Principles of Finance

4 sh

Select one course from the following: 4 sh

STS 3470Statistical Computing for Simulation and Theory

4 sh

FIN 4120Investments

4 sh

FIN 4160Fundamentals of Insurance and Estate Planning

4 sh

FIN 4180Financial Markets and Institutions

4 sh

FIN 4190Financial Planning

4 sh

FIN 4330Derivatives

4 sh

For the Actuarial Science concentration, /sts-3470'>STS 3470 cannot count both as an elective under Major Requirements and as an elective course for the concentration.

Biostatistics: 16 sh

Required course: 4 sh

PHS3010Introduction to Epidemiology

4 sh

The PHS 2010 and PHS 2020 prerequisites for PHS 3010 will be waived for declared statistics majors pursuing the Bachelor of Science degree with the permission of the Public Health Studies Coordinator.

Select three courses from Track A or three courses from Track B: 12 sh

If a 3 sh course has an accompanying 1 sh lab, this lab course must be taken with the course.

Track A

BIO 1112Introductory Cell Biology

3 sh

BIO 1113Cell Biology Laboratory

1 sh

BIO 2212Principles of Genetics

3 sh

BIO 2213Genetics Laboratory

1 sh

BIO 2512Introductory Population Biology

3 sh

BIO 2513Population Biology Laboratory

1 sh

BIO 4212Topics in Advanced Genetics

4 sh

Track B

BIO 1514Biodiversity

4 sh

BIO 2512Introductory Population Biology

3 sh

BIO 2513Population Biology Laboratory

1 sh

BIO 3532The Biology of Animal Behavior

4 sh

BIO 3602/ENS 3460Wetlands Ecology and Management

4 sh

BIO 3612Aquatic Biology: the Study of Inland Waters

4 sh

BIO 3622General Ecology

4 sh

Data Analytics: 16 sh

Required courses: 8 sh

CSC 1300Computer Science I

4 sh

CSC 3211Database Systems

4 sh

Select one course from the following which was not already taken as part of the major requirements: 4 sh

STS 3270Statistical Computing for Data Management

4 sh

STS 3300Statistical Methods for Data Analytics

4 sh

For the Data Analytics concentration, neither of the two computing courses can count as the required core elective course.

Select one course from the following: 4 sh

MTH 2300Mathematical Methods for Data Analytics

4 sh

CSC 2300Computer Science II

4 sh

MEA3290Applied Media Analytics

4 sh

MGT 4250Data Visualization and Storytelling

4 sh

MGT 4260Data Mining for Managerial Decision Making

4 sh

Total Credit Hours: 56-60

All graduating statistics majors are required to satisfactorily complete a senior comprehensive evaluation. This evaluation is not an exam, but it will require students to reflect upon related experiential accomplishments undertaken while completing the major. It is recommended that majors save work from their statistics courses to complete these reflections.

Program Outcomes

Statistics promotes quantitative critical thinking skills that should serve the student in the rest of their course of studies at Elon and in their professional and educational careers after graduation. Upon graduation, students should be able to:

Design and critique strategies for acquiring data —such as sample surveys, experiments, observational studies, and simulations—as appropriate to the investigative context.

Apply statistical concepts to solve real-world problems and interpret results.

Effectively use at least two statistical software or programming languages with an emphasis on computational reproducibility.

Reflect on ethical implications of data-based decisions and technologies.

Clearly and accurately communicate statistical concepts, methods, and results to address specific audiences (technical and non-technical).

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