## Mathematics - Coopersmith Career Consulting

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## Descriptions and credit recommendations for all evaluated learning experiences

Varies (self-study; self-paced).

April 2019 - Present.

Upon completion of this course, students will be able to: specify the domain of a function; determine finite limits and limits at infinity; apply the definition of the derivative and rules for differentiation; solve applications involving derivatives; evaluate definite integrals graphically and using rules of integration; solve applications involving integration; compute derivatives and integrals of logarithmic and exponential functions; and apply techniques of integration to evaluate integrals.

This course provides students a working knowledge of the concepts in calculus. Major topics include: differential and integral calculus; limits, derivatives, rules of differentiation, applications of the derivative, integration, applications of integration, logarithmic and exponential functions, and integration techniques. Instructional methods include: study guide, required readings, and a final exam.

In the lower division baccalaureate/associate degree category OR in the upper division baccalaureate degree category, 3 semester hours in Accounting, Business, Computer Science, Data Sciences, Engineering, Economics, Finance, Marketing, or Mathematics (4/19).

Varies (self-study; self-paced).

June 2017 - Present.

Upon successful completion of this course, students will be able to: convert realistic situations into mathematical concepts so mathematical tools can be used to solve them; use Venn diagrams, graphs, charts and similar methods to represent, organize and analyze data; apply principles of logic to prove or disprove statements (both in text and in mathematical form) on the basis of other given statements; identify, manipulate and utilize mathematical expressions including rational, irrational and imaginary numbers, along with mathematical expressions such as absolute value, inequalities and radicals; use principles of algebra and geometry to identify variables and express algebraic expressions on graphs; determine the probability of a specified event or condition or series of events or conditions; and apply principles of statistics, such as averages, normal distributions and standard deviations to identify statistically significant data.

This course is designed to develop students’ mathematical thinking and reasoning skills though problem-solving. Instruction covers many of the tools in the mathematical toolbox, including concepts in data sets, number systems, algebra, geometry, logic, graphing, probability and statistics. Other topics include: basics of arithmetic, algebra and geometry and related relevant concepts. **Prerequisites**: College Algebra and College Geometry or demonstrable skills in those areas, such as superior scores on standardized tests in those areas.

In the upper division baccalaureate degree category, 3 semester hours in Math, Business, Finance, or as a general elective (6/17) (2/22 revalidation).

Varies (self-study; self-paced).

April 2019 - Present.

Upon completion of this course, students will be able to: solve systems of linear equations and perform operations on vectors; determine if a given set of vectors is linearly independent and perform linear transformations; determine if the inverse of a matrix exists, calculate the inverse of a matrix, and identify geometric changes of matrices; determine if a vector is in a vector space, identify properties of determinants, and apply Cramer’s rule to solve linear systems; determine whether a given set is a vector space or subspace, find a basis for a column space, and map a vector to its coordinate vector in a basis; find the dimension of a subspace, apply the rank theorem, and map a coordinate vector from one base to another; calculate eigenvalues, determine if a vector is an eigenvector, and diagonalize matrices; determine orthogonality projections and orthogonality of vectors; determine symmetry and orthogonality of matrices, find the matrix of a quadratic form; and find the singular values of a matrix.

This course provides students with a working knowledge of the concepts in linear algebra and the underlying theory and applications in linear algebra.Topics include: linear systems, matrix algebra, determinants, vector spaces, eigenvalues and eigenvectors, orthogonality, symmetric matrices, and quadratic forms. Instructional methods include: study guide, required readings, and a final exam.

In the lower division baccalaureate/associate degree category OR in the upper division baccalaureate degree category, 3 semester hours in Accounting, Business, Computer Science, Data Sciences, Engineering, Economics, Finance, Marketing, or Mathematics (4/19).

Varies (self-study; self-paced).

April 2019 - Present.

Upon completion of this course, students will be able to: calculate and use measures of central tendency to draw conclusions about data and organize data graphically; calculate probabilities and apply Bayes’ Theorem; determine continuous and joint probabilities and calculate expected values; perform calculations related to binomial, negative binomial, and Poisson distributions; solve applications involving common continuous distributions; determine the sample size needed to fit a situation and determine probabilities using the sampling distribution of the mean; construct confidence intervals for proportions and variance and determine maximum likelihood estimators; describe type I and type II errors and perform hypothesis tests; fit data using simple linear regression and compute correlation coefficients; and interpret results involving multiple linear regression models.

This course provides students with a working knowledge of the concepts in probability and statistics and the underlying theory and applications. Topics include: probability, discrete distributions, continuous distributions, sampling distributions, point estimation, interval estimation, hypothesis testing, simple linear regression, multiple regression, and nonlinear regression. Instructional methods include: study guide, required readings, and a final exam.

In the lower division baccalaureate/associate degree category OR in the upper division baccalaureate degree category, 3 semester hours in Accounting, Business, Computer Science, Data Sciences, Economics, Finance, or Mathematics (4/19).

Varies (self-study; self-paced).

April 2019 - Present.

Upon completion of this course, students will be able to: describe the use of modeling in quantitative analysis; develop useful and accurate decision trees; formulate and interpret characteristics of linear regression models; compute the economic order quantity (EOQ) and reorder point (ROP) for inventory problems; solve and interpret linear programming models both graphically and algebraically; model and solve maximal-flow, shortest-route, and minimal-spanning tree problems; describe the basic queuing system configurations and all three parts of a queuing system; and analyze simulation models as applied to inventory control and queuing theory.

This course provides students with a working knowledge of the most important basic concepts of quantitative analysis in business and management by teaching various modeling techniques for problems related to business and management. Topics include: decision trees, linear and multivariate regression, inventory methods, linear programming techniques, transportation and network problems, queuing theory, and simulation. Instructional methods include: study guide, required readings, and a final exam.

In the lower division baccalaureate/associate degree category OR in the upper division baccalaureate degree category, 3 semester hours in Accounting, Business, Computer Science, Data Sciences, Economics, Finance, or Mathematics (4/19).