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Course Descriptions

The curriculum of the program in the Department of Mathematics is designed to provide a broad education in both theoretical and applied mathematics. It also develops the scientific knowledge and the problem solving, computing, and communications skills that are critical to a successful mathematically based career.

MA 223 - Engineering Statistics I

  • Credit Hours: 4R-0L-4C
  • Term Available: F,W,S
  • Graduate Studies Eligible: No
  • Prerequisites: MA 112
  • Corequisites: None

This is an introductory course in statistical data analysis. Topics covered include descriptive statistics, introduction to probability concepts, and random variables. A Central Limit Theorem will be presented. Inference (hypothesis testing and confidence intervals) for one mean, two independent means, and two means from a paired sample will be covered. An introduction to one factor analysis of variance and simple linear regression will be presented. Time permitting, inference for a one proportion and one standard deviation/variance are discussed. Both classical methods for inference as well as modern resampling methods are presented. A computer package will be used for statistical analysis and simulation. Experimental data from a variety of fields of interest to the science and engineering majors enrolled will also be used to illustrate statistical concepts and facilitate the development of the student’s statistical thinking. A student cannot take both MA 223 and MA 382 for credit.

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