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Mackinaw Hall on Grand Valley's Allendale Campus.

Applied Statistics, M.S.

Applied statistics is a practical, hands-on program that provides a comprehensive set of applied statistical techniques, which allows students to succeed as applied statisticians in academia and industry.

Visit the program website for more information.

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Program Overview

The Master of Science in applied statistics is a Professional Science Master's program that allows students to combine strong communication skills with an ability to interpret and present statistical findings. The curriculum emphasizes practical experience and statistical applications, so students are ready to make an immediate impact on the applied statistics industry.

The degree emphasizes teamwork, problem-solving communication, scientific knowledge, and technical skills. An internship is required. Visit gvsu.edu/psm for more program information.

Prerequisites

Good performance in undergraduate statistics will strengthen an application. This coursework should include SAS and be equivalent to STA 216 at GVSU. Completion of this course and other statistics courses is recommended either concurrent with an application or later. Some other programming language experience is advantageous as part of an application (R, Python etc.) but it is not required. Quantitative/data-oriented work experience would also be considered relevant but is not required.

Why Study Applied Statistics at Grand Valley?

  • The program offers a comprehensive curriculum in applied statistics at the graduate level, providing experience in a greater variety of applied statistical techniques.
  • Statisticians are in high demand across a variety of industries: retail, manufacturing, health care, and academia.
  • Internships provide valuable, hands-on industry experience sought by employers.
  • Many of the courses are offered in the evening, allowing more flexibility in students' daily schedules.
  • Students gain valuable experience in the application of statistical software.

Career Insights

This tool shows an overview of potential career opportunities for this major. Actual salaries, employment opportunities, and job titles may change over time.

Location & Format

Graduate students in this major study at the Grand Valley Allendale Campus and the Robert C. Pew Grand Rapids Campus.

Format:
  • Face To Face

Coursework

Requirements for the degree are 36 credit hours, comprised of the following components:

  • Twenty-two credit hours in applied statistics courses
  • Elective credit hours
  • Professional science courses
  • Internship experience

Application Deadline

The application deadline for fall semester is June 1; winter deadline is November 1. The $30 nonrefundable application fee is waived if the applicant has previously applied to GVSU.

Admission Requirements

Admission to the PSM in Applied Statistics will be based on a set of application materials. An undergraduate major or minor is not required but strong performance in several undergraduate courses will strengthen the possibility of a successful application. Prerequisite material may be suggested prior to program acceptance. Relevant work experience is also considered in the evaluation of an application. In conjunction with satisfying general graduate GVSU admission policies, the following requirements must be satisfied or included as part of the application: 

  • Grade point average of 3.0 on a 4.0 scale from all undergraduate coursework or a satisfactory score on the GRE. 
  • Resume detailing work experiences and accomplishments. 
  • Personal statement of career goals and background experiences, including an explanation of how this program will help achieve educational and professional objectives. 
  • Letters of recommendations from at least two individuals who are in positions to attest to the applicant’s successful completion of the program.

For More Information

Department of Statistics

Dr. Robert Downer, [email protected]
gvsu.edu/stat
A-1-178 Mackinac Hall | (616) 331-3355

Graduate Admissions Office

gvsu.edu/gradapply

 

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