## ##   * Overview
  * Program Requirements
The Master of Science in Statistics—Connect program is designed for students
from all backgrounds with a BS/BA degree, provided the student has experience
with basic calculus and statistics. The first semester of the degree program
provides students with the foundational knowledge needed to study successfully
alongside direct-entry graduate students. The field of statistics plays a
critical role in the support of nearly every industry including technology;
business, management, and finance; healthcare and pharmaceuticals; and more.
The MS in Statistics develops a comprehensive and flexible skill set that
allows graduates to adapt to an ever-changing job market in various
occupations and industries. In an era of increasing automation of Big Data,
the value of the rigor of statistical thinking and analysis by individuals
grows with the rise of automated Big Data analysis (e.g., artificial
intelligence and machine learning). This program in statistics is designed to
provide learners with a solid foundation in applied, modern, and computational
approaches to statistical analysis and exposure to the statistical thinking
skills necessary to critically assess data and answer business and research
questions across domains. Core courses integrate theory and application,
enabling students to be ready for the job on day one. Upon application, each
student selects an industry concentration (biostatistics, statistical machine
learning, and statistical theory and modeling) to examine statistical theories
and applied methodologies most relevant to specific career pathways. In this
degree program, students are admitted to the college associated with their
concentration, and their degree is awarded by that college. The concentrations
are associated with the following colleges:
  * Biostatistics—Bouvé College of Health Sciences
  * Statistical Machine Learning—Khoury College of Computer Sciences
  * Statistical Theory and Modeling—College of Science
Students will follow all policies associated with their college. Each student
finishes the program with experiential courses such as a thesis, capstone, or
consulting project, where they gain hands-on, project-based experience
addressing business problems and presenting and communicating the findings and
recommendations.
* * *
  * Concentrations and course offerings may vary by campus and/or by program modality. Please consult with your advisor or admissions coach for the course availability each term at your campus or within your program modality.
  * Certain options within the program may be  _required_ at certain campuses or for certain program modalities. Please consult with your advisor or admissions coach for requirements at your campus or for your program modality. 
* * *
Complete all courses and requirements listed below unless otherwise indicated.
## Connect Courses
Course List Code | Title | Hours  
---|---|---  
Students are required to complete 8–10 semester hours from the following
unless otherwise determined by the program:| 8-10  
[CS 5001](/search/?P=CS%205001 "CS 5001")| Intensive Foundations of Computer
Science|  
[MATH 5001](/search/?P=MATH%205001 "MATH 5001")| Accelerated Linear Algebra|  
[MATH 5002](/search/?P=MATH%205002 "MATH 5002")| Accelerated Multivariable
Calculus|  
[MATH 5003](/search/?P=MATH%205003 "MATH 5003")| Accelerated Probability and
Statistics|  
[MATH 5110](/search/?P=MATH%205110 "MATH 5110")| Applied Linear Algebra and
Matrix Analysis|  
## Required Courses
Course List Code | Title | Hours  
---|---|---  
[MATH 5010](/search/?P=MATH%205010 "MATH 5010")| Foundations of Statistical
Theory and Probability| 4  
[MATH 6241](/search/?P=MATH%206241 "MATH 6241")| Stochastic Processes| 2  
[MATH 6243](/search/?P=MATH%206243 "MATH 6243")| Statistical Learning| 4  
[PHTH 6800](/search/?P=PHTH%206800 "PHTH 6800")| Causal Inference in Public
Health Research| 3-4  
or [PHTH 6801](/search/?P=PHTH%206801 "PHTH 6801")|  Causal Inference 1  
[PHTH 6830](/search/?P=PHTH%206830 "PHTH 6830")| Generalized Linear Models| 4  
## Concentrations
Complete one of the following concentrations:
  * Biostatistics ([Bouvé College of Health Sciences](http://northeastern.edu/bouve))
  * Statistical Machine Learning ([Khoury College of Computer Sciences](https://khoury.northeastern.edu/))
  * Statistical Theory and Modeling ([College of Science](http://www.northeastern.edu/cos))
## Experiential Courses
Course List Code | Title | Hours  
---|---|---  
Complete 2 semester hours from the following (courses can be repeated):| 2  
[MATH 6910](/search/?P=MATH%206910 "MATH 6910")| Master's Project|  
[PHTH 6880](/search/?P=PHTH%206880 "PHTH 6880")| Statistical Consultancy|  
## Co-op (Optional)
Course List Code | Title | Hours  
---|---|---  
Co-op Preparation|  
[MATH 6000](/search/?P=MATH%206000 "MATH 6000")| Professional Development for
Co-op| 0  
Co-op Work Experience|  
_Statistical Machine Learning Concentration Students_|  
Statistical machine learning students may take either course.|  
_Biostatistics Concentration Students_|  
[HLTH 6964](/search/?P=HLTH%206964 "HLTH 6964")| Co-op Work Experience|  
_Statistical Theory and Modeling Concentration Students_|  
[MATH 6964](/search/?P=MATH%206964 "MATH 6964")| Co-op Work Experience|  
## Program Credit/GPA Requirements
32–35 total semester hours required
Minimum 3.000 GPA required
* * *
### Biostatistics Concentration (Bouvé College of Health Sciences)
Course List Code | Title | Hours  
---|---|---  
Complete 12 semester hours from the following:| 12  
[PHTH 5350](/search/?P=PHTH%205350 "PHTH 5350")| Using SAS in Public Health
Research|  
[PHTH 6440](/search/?P=PHTH%206440 "PHTH 6440")| Advanced Methods in
Biostatistics|  
[PHTH 6802](/search/?P=PHTH%206802 "PHTH 6802")| Causal Inference 2|  
[PHTH 6810](/search/?P=PHTH%206810 "PHTH 6810")| Survival Analysis|  
[PHTH 6820](/search/?P=PHTH%206820 "PHTH 6820")| Design and Analysis of
Clinical Trials|  
###  Statistical Machine Learning Concentration (Khoury College of Computer
Sciences)
Course List Code | Title | Hours  
---|---|---  
[CS 5100](/search/?P=CS%205100 "CS 5100")| Foundations of Artificial
Intelligence| 4  
[CS 6140](/search/?P=CS%206140 "CS 6140")| Machine Learning| 4  
[DS 5110](/search/?P=DS%205110 "DS 5110")| Introduction to Data Management and
Processing| 4  
### Statistical Theory and Modeling Concentration (College of Science)
Course List Code | Title | Hours  
---|---|---  
Complete 12 semester hours from the following:| 12  
[MATH 7339](/search/?P=MATH%207339 "MATH 7339")| Machine Learning and
Statistical Learning Theory 2|  
[MATH 7340](/search/?P=MATH%207340 "MATH 7340")| Statistics for
Bioinformatics|  
[MATH 7341](/search/?P=MATH%207341 "MATH 7341")| Probability 2|  
[MATH 7342](/search/?P=MATH%207342 "MATH 7342")| Mathematical Statistics|  
[MATH 7343](/search/?P=MATH%207343 "MATH 7343")| Applied Statistics|  
[MATH 7344](/search/?P=MATH%207344 "MATH 7344")| Regression, ANOVA, and
Design|