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Course Criteria
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3.00 Credits
Opportunity to offer courses in areas of departmental general education interest not covered by the regular general education courses.
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1.00 Credits
Covers theories of learning mathematics, state standards, and educational issues related to teaching and learning mathematics. Students will spend an average of two to three hours each week in a public school mathematics classroom. The first half of the semester will be spent in a middle school classroom and the second half of the semester will be spent in a high school classroom. Classroom settings will include urban and suburban or rural locations with students having diverse learning needs. Activities in the field will include tutoring, interviewing, and helping the cooperating teacher with a variety of classroom tasks.
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3.00 Credits
Designed to strengthen mathematical content knowledge of students majoring in middle-level (grades 4 to 8) education. Focus on topics such as the rational and real number systems; number theory; two- and three-dimensional shapes; spatial reasoning; and the display, interpretation, and use of data representations. Prerequisite: math placement level of 2 or above.
Prerequisite:
MATH 105, MATH 117, or Math Placement Test Score of 2 or Higher
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4.00 Credits
Introduction to study of differential and integral calculus from algebraic, numerical, and graphical points of view. Concept of limit and applications of derivatives will be covered. Prerequisite: math placement level 6.
Prerequisite:
MATH 124 (Grade of C or Higher), MATH 175 (Grade of C or Higher), or Math Placement Test Score of 6 or Higher
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4.00 Credits
Continuation of Calculus I. Will include methods of integration, applications and infinite series.
Prerequisite:
MATH 211 (Grade of C or Higher)
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4.00 Credits
Generalization of single-variable calculus to higher dimensions. Parametric curves and applications covered.
Prerequisite:
MATH 212
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4.00 Credits
Topics include exploratory data analysis, basic probability, the Central Limit Theorem, confidence intervals, hypothesis testing, linear regression, experimental design, analysis of variance and goodness of fit tests. A statistical software package will be utilized throughout course. Prerequisite: Math Placement Level 5 or higher.
Prerequisite:
MATH 175 or Math Placement Test Score of 5 or Higher
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3.00 Credits
This is the first semester of a two-semester sequence in Data Science. Using real-world examples of wide interest and a popular programming language such as R or Python, we introduce methods for key facets of a data-driven investigation. These include obtaining data from a variety of sources, wrangling the data to get a manageable data set, exploratory data analysis to generate hypotheses and intuition about the data, and communication of results through interpretable summaries that are both transparent and reproducible.
Prerequisite:
(CMSC 104, CMSC 110, ENGR 110, ENGR 120, ITAN 240, or SWEN 100) and (MATH 117 (Grade of C or Higher), MATH 217 (Grade of C or Higher), MATH 375 (Grade of C or Higher), or SCMG 200 (Grade of C or Higher))
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4.00 Credits
Study of topics usually associated with analysis of discrete and/or finite mathematical models. Topics from logic, set theory, Boolean algebra, mathematical proof, recursion, induction, combinatorics, discrete probability, matrices and graph theory covered. Prerequisite: math placement level 4 or above.
Prerequisite:
MATH 140, MATH 175, MAT 181, MATH 211, or Math Placement Test Score of 4 or Higher
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3.00 Credits
Study of statistical methods and their application to various data sets. The entire statistical process of data collection, fitting data to a model, analysis of the model, verification of the model, and inference will be covered. Topics include non-parametric statistics, multiple linear regression, ANOVA, experimental designs, categorical data analysis, logistic regression, time series, and survival analysis. Examples taken from a variety of disciplines. Concepts reinforced through class projects. A statistical software package will be utilized throughout the course.
Prerequisite:
MATH 217 (Grade of C or Higher), MATH 313 (Grade of C or Higher), or MATH 375 (Grade of C or Higher)
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