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Statistics

The Bachelor of Science degree in Statistics is designed to provide foundations that include basic statistical concepts and methodologies, and to expose students to the role of statistical thinking and analysis in interdisciplinary research and in the public sphere. To ensure deep rigorous understanding of the foundations and main methods of analysis in statistics, the program is composed of three parts: a) foundations in mathematics and computing, combined with an introduction to statistical thinking and practice; b) four core courses on the fundamentals of statistical theory and data analysis; and c) more advanced material covering important areas of statistical methodology. A capstone project involving substantial data analysis or focused on methodology/theory is required. Students also have opportunities to acquire practical experience in study design, data management, and statistical analysis by working as undergraduate research assistants in projects in one of the participating academic departments or Research Centers at Brown.

The Concentration is based on several premises: that statistics is a scientific discipline in its own right, with specialized methodologies and body of knowledge; that it is essentially concerned with the art and science of data analysis; and that it is best taught in conjunction with specific, substantive applications. To this end, the Concentration is designed to provide foundations that include basic statistical concepts and methodologies, and to expose students to the role of statistical thinking and analysis in interdisciplinary research and in the public sphere.  The Concentration prepares students for careers in industry and government, for graduate study in statistics or biostatistics and other sciences, as well as for professional study in law, medicine, business, or public administration. The undergraduate concentration guide is available here

The Undergraduate Concentration in Statistics is administered by the Department of Biostatistics and leads to a Sc.B. degree. To ensure deep rigorous understanding of the foundations and main methods of analysis in statistics, the program is composed of three parts. The first part entails foundations in mathematics and computing, combined with an introduction to statistical thinking and practice. The second part includes four core courses that provide a comprehensive account of the fundamentals of statistical theory and data analysis. The third part delves into more advanced material covering important areas of statistical methodology. In addition to the formal coursework, students are required to complete a capstone project that involves a substantial data analysis or a methodological/theoretical project.  Students also have opportunities to acquire practical experience in study design, data management, and statistical analysis by working as undergraduate research assistants in projects in one of the participating academic Departments or Research Centers at Brown. 

The program requires thirteen one-semester courses. The required courses are as follows:

LEVEL I: Foundations in Mathematics - Calculus2
Single Variable Calculus, Part II
Multivariable Calculus
LEVEL I - Foundations in Mathematics - Linear Algebra1
Linear Algebra
Computing1
Introduction to Scientific Computing
Introduction to Scientific Computing and Problem Solving
Introduction to Statistical Thinking and Practice1
Essentials of Data Analysis
With the approval of the Director of the Statistics Concentration, one of the following courses may serve as replacement:
Introductory Statistics for Social Research
Introduction to Econometrics
Essential Statistics
Statistical Analysis of Biological Data
Statistical Methods
LEVEL II - Core Courses in Theory and Data Analysis2
Statistical Inference I
Honors Statistical Inference I
Statistical Inference II
OR
Probability
Mathematical Statistics
Introduction to Biostatistics1
Principles of Biostatistics and Data Analysis
OR
Principles of Biostatistics and Data Analysis
LEVEL III: Advanced Courses in Statistical Methods2
Statistical Programming in R
OR
Statistical Programming with R
AND
Applied Regression Analysis
OR
Applied Regression Analysis
Capstone Project1
Independent Study
Electives in Social Science and Biostatistics (Students must choose 2)2
Market and Social Surveys
Principles and Methods of Geographic Information Systems
Techniques of Demographic Analysis
Machine Learning
Computational Molecular Biology
Algorithmic Foundations of Computational Biology
Data Science
Fundamentals of Epidemiology
Clinical Trials Methodology
Introduction to Methods in Epidemiologic Research
Intermediate Methods in Epidemiologic Research
Fundamentals of Probability and Statistical Inference
Statistical Inference I
Bayesian Statistical Methods
Practical Data Analysis
Statistical Inference II
Analysis of Lifetime Data
Linear Models
Causal Inference and Missing Data
Statistical Methods in Bioinformatics, I
Quantitative Models of Biological Systems
Inference in Genomics and Molecular Biology
Operations Research: Probabilistic Models
Computational Probability and Statistics
Information Theory
Recent Applications of Probability and Statistics
Graphs and Networks
Recent Applications of Probability and Statistics
Pattern Recognition and Machine Learning
Introduction to Programming for the Mind, Brain and Behavior
Computational Cognitive Neuroscience
Health Economics
Mathematical Econometrics I
Mathematical Econometrics II
Big Data
Applied Algebraic Topology
Other Analytical/Computational/ Statistical courses with the approval of the Director of the Statistics Concentration
Total Credits13

Prospective students will be able to obtain Advanced Placement credit for the requirements in mathematics. Students who have already completed an introductory course in statistics will be granted permission to proceed to Level II core courses if they meet the prerequisites in mathematics and computing.

PHP 0100: As part of the capstone course or thesis, students should complete an online course, PHP 0100, at their own pace. This course is a requirement and is meant to give a broad overview of public health and it allows students to see different areas in public health where statistics is being used. The course does not require any additional credit and is completed as part of the independent study, PHP 1970/1980. Students who are in a double concentration in public health are exempt from this course.

Senior Thesis: A senior honors thesis is not a requirement for graduation, but concentrators who choose to write one are required to write a manuscript that describes a major project of statistical data analysis that they performed or a simulation study to evaluate the performance of a statistical method. Students that decide to write an honor thesis will generally integrate their capstone project into their thesis. Generally, writing a senior thesis includes two semesters of independent study (PHP 1980), the capstone project may serve as one of those.

Honors: Statistics requires the completion of a senior thesis and a superior record in the program. 

Study Abroad/Study Away: Up to two courses taken elsewhere (study abroad or other transfer) may be applied to required courses. Meet with a concentration adviser to discuss; provide a syllabus for each course to be considered for transfer to your concentration plan.

The program is administered by the Department of Biostatistics, located at 121 South Main Street, 7th floor.

For additional information please contact: Roee Gutman, Box G-S-121-7; Telephone: 401-863-2682; Fax: 401-863-9182; e-mail: Roee Gutman