Bachelor of Science in Industrial Mathematics and Statistics Undergraduate Programme By West Virginia University |TopUniversities
Main Subject Area

MathematicsMain Subject Area

Programme overview

Main Subject

Mathematics

Degree

Other

Study Level

Undergraduate

The curriculum in industrial mathematics and statistics (IMS) provides students with the critical skills and knowledge needed to apply both statistics and mathematics to industrial and scientific problems. IMS is concerned with the mathematical, statistical, and computer modeling of various physical, biological, and social processes. Graduates will be trained to work in business, industry, and government, or they will be able to pursue a graduate degree in any of the mathematical sciences. Industrial mathematics and statistics is vital to our economic competitiveness and is critical to the development of our increasingly scientific/technological society. Industrial mathematics and statistics is built on a foundation of differential/integral calculus, differential equations, applied probability, and statistics. The mathematical tools encompass linear algebra, numerical analysis, continuous models rooted in differential equations, and discrete models linked to finite mathematical structures and Markov processes. Scientific computing extends the rudiments of programming into data visualization, the development of algorithms, and selected topics using high-level languages. Statistical topics especially relevant to industrial and scientific applications include design and analysis of experiments, statistical models, sequential analysis, reliability models, and time series analysis. These statistical methodologies are grounded in fundamental concepts of statistics and probability such as discrete and continuous probability distributions, stochastic processes, estimation and hypothesis testing, and exponential family models. Major Learning Goals Upon successful completion of the B.S. degree, Industrial Mathematics and Statistics majors will be able to: Demonstrate competence in one-variable calculus before proceeding to upper-level courses. Read and interpret mathematical/statistical industrial and scientific word problems. Demonstrate the ability to construct and understand mathematical/statistical models in science and engineering. Research an industrial or scientific problem by reading mathematical/statistical articles and texts. Develop a solution to the aforementioned industrial or scientific problem. Write and present an applied research report on the industrial or scientific problem. Careers Computer Science Economics Engineering Mathematics Technology Statistics

Programme overview

Main Subject

Mathematics

Degree

Other

Study Level

Undergraduate

The curriculum in industrial mathematics and statistics (IMS) provides students with the critical skills and knowledge needed to apply both statistics and mathematics to industrial and scientific problems. IMS is concerned with the mathematical, statistical, and computer modeling of various physical, biological, and social processes. Graduates will be trained to work in business, industry, and government, or they will be able to pursue a graduate degree in any of the mathematical sciences. Industrial mathematics and statistics is vital to our economic competitiveness and is critical to the development of our increasingly scientific/technological society. Industrial mathematics and statistics is built on a foundation of differential/integral calculus, differential equations, applied probability, and statistics. The mathematical tools encompass linear algebra, numerical analysis, continuous models rooted in differential equations, and discrete models linked to finite mathematical structures and Markov processes. Scientific computing extends the rudiments of programming into data visualization, the development of algorithms, and selected topics using high-level languages. Statistical topics especially relevant to industrial and scientific applications include design and analysis of experiments, statistical models, sequential analysis, reliability models, and time series analysis. These statistical methodologies are grounded in fundamental concepts of statistics and probability such as discrete and continuous probability distributions, stochastic processes, estimation and hypothesis testing, and exponential family models. Major Learning Goals Upon successful completion of the B.S. degree, Industrial Mathematics and Statistics majors will be able to: Demonstrate competence in one-variable calculus before proceeding to upper-level courses. Read and interpret mathematical/statistical industrial and scientific word problems. Demonstrate the ability to construct and understand mathematical/statistical models in science and engineering. Research an industrial or scientific problem by reading mathematical/statistical articles and texts. Develop a solution to the aforementioned industrial or scientific problem. Write and present an applied research report on the industrial or scientific problem. Careers Computer Science Economics Engineering Mathematics Technology Statistics

Admission Requirements

61+
6+

Scholarships

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