Rochester Institute of Technology

Kate Gleason College of Engineering

Statistical Methods for Product and Process Improvement (Adv. Certificate)

Address:

One Lomb Memorial Drive

Rochester, NY 14623

United States

Phone:

1-866-260-3950

Fax:

585-475-7164

Program Information

Degrees Offered:

Statistical Methods for Product and Process Improvement (Adv. Certificate)

Format: Campus

Program Description:

This advanced certificate is designed for engineers, scientists, and similar professionals who want a sound education in statistical methods but who wish to finish a program in a shorter time period than that for the MS degree in applied statistics. Graduates of this program will be able to characterize variation in their processes through ANOVA; model processes through regression; and optimize processes through experimental design. Based on electives, graduates may also be able to construct robust processes and products, perform advanced experimental design techniques, create time series models, study multivariate relationships, or investigate reliability of products.



Credit earned through this certificate may be applied toward the MS in applied statistics.



The program is available part-time, on campus or online, and consists of 18 credit hours (six courses).

Accreditation:

.

International Student Requirements:

International students whose native language is not English must have a TOEFL score of at least 550 (or a computer-based TOEFL of at least 213).

Facts & Figures

International Financial Aid: Yes

International Financial Aid Description: For graduate study, many of the 70 graduate programs offer assistantships. Additionally, more than 9,000 student jobs are available on campus each year.

# of Credits Required: 18

Classification: Master's College or University I

Loans Offered: Loans may be available. Applicants may apply by completing the Free Application for Federal Student Aid (FAFSA). Candidates may work with RIT's Financial Aid Office to determine aid eligibility and funding options.

Locale: Large Suburb

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