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CPSC 1301. Computer Science 1 (3-0-3) Co-requisite: CPSC 1301L. This course includes an overview of computers and programming; problem solving and algorithm development; simple data types; arithmetic and logic operators; selection structures; repetition structures; text files; arrays (one-and-two-dimensional); procedural abstraction and software design; modular programming (including sub-programs or the equivalent).


MATH 1131. Calculus with Analytic Geometry 1 (4-0-4) Prerequisite: MATH 1113 with a grade of "C" or better or an appropriate math placement score. Topics include exponential and logarithmic functions, introduction to limits and derivatives, computation and application of derivatives, and the definite integral. (Course fee required.)


MATH 1132. Calculus with Analytic Geometry 2 (4-0-4) Prerequisite: MATH 1131 with a grade of "C" or better. Topics include the definite and indefinite integrals, improper integrals, techniques of integration, applications of integration, and infinite sequences and series. (Course fee required.)


MATH 2135. Calculus with Analytic Geometry 3 (4-0-4) Prerequisite: MATH 1132 with a grade of "C" or better. Topics include parametric equations and polar coordinates, vectors, dot and cross products, vector functions of one real variable, real valued functions of several variables, differential calculus of functions of several variables, and multiple integrals.


MATH 2115. Introduction to Linear Algebra (3-0-3) Prerequisite: MATH 1131 may be taken concurrently. Systems of linear equations, matrix algebra, vector spaces, bases for a vector space, linear transformations, eigenvalues and eigenvectors, and matrix decompositions.


STAT 1127. Introductory Statistics (3-0-3) Prerequisite: Satisfactory score on math placement exam or completion of any of the following courses with a grade of "C" or better: MATH 1001, MATH 1101, MATH 1111, MATH 1113, MATH 1125, or MATH 1131. Survey of modern statistical methods applicable to behavioral, biological, health and managerial sciences, and education. Organization and analysis of data, probability distributions, sampling distributions, point estimation, confidence interval, hypothesis testing, and regression analysis. (Course fee required.)