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Course Criteria
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4.00 Credits
Systems of linear equations, matrix algebra and determinants; real vector spaces, linear independence, basis and dimension; real inner product spaces, Gram-Schmidt orthogonalization; eigen theory and diagonalization; linear transformations and matrix representation.
Prerequisite:
MATH 311; MATH 310/520 recommended.
Corequisite:
MATH 311; MATH 310/520 recommended.
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4.00 Credits
A rigorous one-semester study of probability, distribution theory and the basics of statistical inference. Topics include probability, expectation, discrete and continuous distributions, descriptive statistics and both estimation and hypothesis testing for one- and two-sample problems.
Prerequisite:
MATH 311.
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3.00 Credits
Algebraic properties of complex number systems, set theory, groups, rings, integral domains and fields. MATH 310/520 and MATH 322/502.
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4.00 Credits
Study of geometry from both classical and transformational points of view. The classical part will focus on the axiomatic development of various forms of geometry; the transformational part will focus on the study of geometry in terms of two families of transformations: isometries and similarities. Emphasis on investigating geometry using both classical and transformational approaches and their interactions.
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3.00 Credits
Real number system, limits of sequences and functions, theory of differentiation, Reimann integration, infinite series.
Prerequisite:
MATH 310/520, 311, 322/502. MATH 345/504 recommended.
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3.00 Credits
Theory of inference, symbolic logic, nature of axiom systems, validity of proofs, consistency, independence, completeness, theory of sets and cardinal numbers.
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3.00 Credits
Survey of statistical methods used in research, education, behavioral science and biomedical applications. Experimental designs discussed regarding advantages, disadvantages, sampling problems and analysis. Regression and analysis of variance. Prereq: An elementary probability or statistics course.
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3.00 Credits
Continuation and extension of statistical methods introduced in Statistical Methods I (Math 535). Advanced topics in analysis of variance, randomized block designs and experimental designs. Prereq: Math 535 or permission of instructor.
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1.00 Credits
Capstone course designed to serve as outcome assessment for math majors enrolled in statistics option. Course involves problem solving, data analysis and statistical consulting. Materials drawn from real-world problems.
Prerequisite:
Math 535.
Corequisite:
Math 536.
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3.00 Credits
Complex number system, analytic functions, elementary functions, contour integration, residues and poles, conformal mapping.
Prerequisite:
MATH 506 or equivalent.
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