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Course Criteria
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3.00 Credits
Students will acquire the knowledge and skills used in data science at an introductory level. The course will focus on interaction between statistical and mathematical reasoning and their application to the collection, preparation, and presentation of data and underlying data management skill for such analysis. Access to a computer is required.
Prerequisite:
A02 23 and MATH 1010
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3.00 Credits
Basic concepts of probability and statistics including data collection and analysis, correlation and regression, probability, discrete and continuous distributions (binomial, normal and t distributions), estimation and hypothesis testing, with an emphasis on applications and understanding of the main ideas.
Prerequisite:
A02 21 and ALEKS 46 and ALEKSC 46 and D01 20 and MATH 1010 and MATH 1050 and MATH 1080 and MATH 1210 and MME3 080
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1.00 Credits
Solving mathematics problems at the appropriate level for students' backgrounds using a computer algebra system.
Prerequisite:
MATH 1050 and MATH 1060 and MATH 1080 and MATH 1210
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4.00 Credits
Limits, continuity, differentiation, integration.
Prerequisite:
ALEKS 78 and D01 90 and MATH 1050 and MATH 1060 and MATH 1080
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4.00 Credits
Definite, indefinite, and improper integrals, trancendental fuctions, inverse functions, techniques of integration, applications of integration.
Prerequisite:
MATH 1210
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4.00 Credits
Transcendental functions, techniques of integration, analytic geometry, infinite series.
Prerequisite:
APM1 4 and APM2 3 and MATH 1210
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4.00 Credits
An overview of the fundamentals of algorithmic, discrete mathematics applied to computation using a contemporary programming language. Topics include logic, proofs, sets, functions, counting, relations, graphs, trees, Boolean algebra, and models of computation. This course includes programming.
Prerequisite:
CS 1400 and MATH 1050 and MATH 1080
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1.00 - 6.00 Credits
Topics from mathematics which convey to the student the beauty and utility of mathematics, and which illustrate its application to modern society. Mathematical material in this course will center on topics including: proportional reasoning, linear and exponential modeling, geometry, scaling factors, probability and expectations, statistical inference, and financial mathematics. Material will be introduced to students in the form of a real life problem and the mathematics necessary to solve that problem will be developed. Consult the semester class schedule for the current offering under this number. The specific title and credit authorized will appear on the student transcript.
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3.00 Credits
Prospective school teachers revisit mathematics topics from the K-8 school curriculum and examine them from an advanced perspective including arithmetic, number theory, and problem solving.
Prerequisite:
A02 23 and ALEKS 46 and D01 20 and MATH 0970 and MATH 1010 and MATH 1030 and MATH 1035 and MATH 1040 and MATH 1050 and MATH 1060 and MATH 1080 and MME3 080 and PMC 4
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3.00 Credits
Prospective school teachers revisit mathematics topics from the K-8 school curriculum and examine them from an advanced perspective including variables, expressions, equations and inequalities, and functions. This course includes recitation and hands on activities. The goal is to present mathematical concepts and effective teaching strategies in an integrated manner. Underlying goals are to stimulate variety in solution processes, provide concrete, pictorial and abstract models, develop communication, collaboration and math reading skills in an environment rich with manipulatives and technology.
Prerequisite:
MATH 2010
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