An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation
Data analysis and measures of central tendency, dispersion, and correlation. Introduction to probability. Estimation and hypothesis testing. Bivariate regression. ANOVA. Introduction to nonparametric techniques. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.
Limits, continuity, differentiation, and applications including exponential, logarithmic, trigonometric, and inverse functions. Mean value theorem, curve sketching, Riemann sums, and the fundamental theorem of calculus. Prerequisite: 2 years high school algebra. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.
Integration techniques and applications, polar coordinates, improper integrals, sequences and series of real numbers, and power series. Prerequisite: MATH1510.
Conic sections, vectors in space, functions of several variables, partial differentiation, multiple integration, line integrals, and Green’s Theorem. Prerequisite: MATH1520.
Foundations of Euclidean and non-Euclidean geometries. Prerequisite: MATH1510 and MATH2350 or consent of instructor. +This course is only offered every other year.
Matrices, vector spaces, linear transformations. Prerequisite: MATH1510 and MATH2350. +This course is only offered every other year.
A study of the objectives, methods, techniques, materials, and activities related to teaching science and mathematics in the secondary schools. Prerequisite: 20 hours in science or mathematics and Prerequisites: admittance into Teacher Education, unless part of an approved Liberal Studies Program.
Introduction to probability, classical probability models and processes, random variables, conditional probability, bivariate distributions and their development, goodness of fit tests, and other nonparametric methods. Prerequisite: MATH1520 and MATH2350. +This course is only offered every other year. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5340 Probability and Statistical Inference.)
An introduction to the fundamentals of computer programming through extensive practice developing software in the Python language. Fundamental terminology and topics such as integrated development environments, variables, data types, control structures, functions, and objects will be covered. ELO4 Global Learning - Innovation
Data analysis and measures of central tendency, dispersion, and correlation. Introduction to probability. Estimation and hypothesis testing. Bivariate regression. ANOVA. Introduction to nonparametric techniques. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.
Limits, continuity, differentiation, and applications including exponential, logarithmic, trigonometric, and inverse functions. Mean value theorem, curve sketching, Riemann sums, and the fundamental theorem of calculus. Prerequisite: 2 years high school algebra. ELO6 Math, GE2B Foundational Skills-Mathematics/Quantitative.
Integration techniques and applications, polar coordinates, improper integrals, sequences and series of real numbers, and power series. Prerequisite: MATH1510.
Conic sections, vectors in space, functions of several variables, partial differentiation, multiple integration, line integrals, and Green’s Theorem. Prerequisite: MATH1520.
Foundations of Euclidean and non-Euclidean geometries. Prerequisite: MATH1510 and MATH2350 or consent of instructor. +This course is only offered every other year.
Matrices, vector spaces, linear transformations. Prerequisite: MATH1510 and MATH2350. +This course is only offered every other year.
A study of the objectives, methods, techniques, materials, and activities related to teaching science and mathematics in the secondary schools. Prerequisite: 20 hours in science or mathematics and Prerequisites: admittance into Teacher Education, unless part of an approved Liberal Studies Program.
Introduction to probability, classical probability models and processes, random variables, conditional probability, bivariate distributions and their development, goodness of fit tests, and other nonparametric methods. Prerequisite: MATH1520 and MATH2350. +This course is only offered every other year. (Students participating in the 4+1 Masters program in Data Science and Analytics should sign up for DSCI5340 Probability and Statistical Inference.)
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