Graduate Certificate Programs


Department of Mathematics and Statistics

Program Description

This certificate is ideal for engineers and scientists who wish to enhance their statistical and data analytic skills . These skills are essential ingredients for success in a data centric world, especially for engineers and scientists.  

The certificate consist of one required course  that provides the fundamentals on probability concepts and distributional  theory, which are essential for gaining a proper understanding of the applied statistical methods and techniques widely used in the analysis of experimental and observational dada . This required course should be  supplemented by three  applied statistics courses selected from the pool of courses listed in the curriculum section below.

To obtain the Graduate Certificate in Statistics through distance education students must complete the following courses to satisfy the stipulated requirements while maintaining a 3.0 cumulative grade point average.


  •  STAT 5643: Probability and Statistics

Choose three courses from the following:

  • STAT 5346 Regression Analysis
  • STAT 5353 Statistical Data Analysis
  • STAT 6239 Clustering Algorithms
  • STAT 6344 Design and Analysis of Experiments

STAT 5643 Probability and Statistics
Introduction to the theory of probability and its applications, sample spaces, random variables, binomial, Poisson, normal distributions, derived distributions, and moment generating functions. Prerequisite: MATH 2222.

STAT 5346/COMP SCI 5204 Regression Analysis
Simple linear regression, multiple regression, regression diagnostics, multicollinearity, measures of influence and leverage, model selection techniques, polynomial models, regression with autocorrelated errors, introduction to non-linear regression. Prerequisites: MATH 2222 and one of STAT 3111, 3113, 3115, 3117, or 5643. (Co-listed with COMP SCI 5204).

STAT 5353 Statistical Data Analysis
Introduction to methods for analyzing statistical data from experiments and Introduction to methods for analyzing statistical data from experiments and surveys. Analysis of variance, correlation, introduction to regression techniques, contingency tables, non-parametric techniques and introduction to modern statistical software. Prerequisites: MATH 2222 and one of STAT 1115, 3113, 3115 and 3117.

STAT 6239 Clustering Algorithms
An introduction to cluster analysis and clustering algorithms rooted in computational intelligence, computer science and statistics. Clustering in sequential data, massive data and high dimensional data. Students will be evaluated by individual or group research projects and research presentations. Prerequisite: At least one graduate course in statistics, data mining, algorithms, computational intelligence, or neural networks, consistent with student's degree program. (Co-listed with COMP ENG 6330, ELEC ENG 6340, SYS ENG 6214 and COMP SCI 6405).

STAT 6344 Design And Analysis Of Experiments
Experimental designs and their statistical analysis. Includes completely randomized designs, complete and incomplete blocking designs, factorial and fractional factorial experiments, multiple comparisons, response surface analysis. Prerequisites: One of STAT 5353, ENG MGT 5715 and one of STAT 3111, 3113, 3115, 3117, 5643; or STAT 5643 and one of STAT 3111,3113, 3115, 3117.

The graduate certificate program is open to all individuals holding a BS degree in mathematics,statistics, or in an engineering or hard scientific discipline with a B average or better in coursework taken for the BS degree. In addition, the applicant must have a minimum of two years of professional experience or currently be accepted into a graduate degree program at Missouri S&T.

Students, who are admitted to the certificate program but not currently enrolled in a graduate degree program at Missouri S&T, will have non-degree graduate status. Students earn graduate credit for the courses they complete. The courses in the certificate program will be offered such that students can complete the program in a timely manner. The certificate courses taken by students admitted to the program will count toward any graduate degree offered by the Department of Mathematics and Statistics, if approved by the student’s academic committee.

Once admitted to the program, a student will be given three years to complete the program as long as a 3.0 grade point average is maintained in the courses taken.

Graduate certificates were designed as a gateway to a master’s degree. If a student earns a B or better in each certificate course they may continue for the graduate degree (in the corresponding department), without needing to submit GRE scores, or letters of recommendation. A student does not need to continue on for the graduate degree, however most do. Graduate certificates were designed for working professionals who have real-life work experience and may not have time to take the GRE/GMAT. Admission requirements for the graduate certificate program are also more relaxed than the graduate degree. This graduate certificate may act as a gateway to the following master’s programs:

Gainful Employment Program Disclosure

Effective July 1, 2011, the Department of Education requires that all certificate programs must disclose particular Gainful Employment information to current and prospective students. The information that is provided in the disclosure includes the estimated cost of the certificate program as well as on-time graduation and job placement rates for this particular certificate program. The disclosure information is based on data from the 2015-16 school year (defined as the period between July 1, 2015, and June 30, 2016)


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Mathematics and Statistics

Dr. VA Samaranayake (Dr. Sam)
Curators' Distinguished Teaching Professor

302 Rolla Building
Missouri University of Science and Technology
Rolla, MO  65409-0020

Phone: (573) 341-4658
Fax: (573) 341-4741


Global Learning - Distance Education 
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Rolla, MO 65409-1560
Phone: 573-341-6591
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