|
|
|
|
|
|
|
Course Criteria
Add courses to your favorites to save, share, and find your best transfer school.
-
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:
MAT 217 FOR LEVEL U WITH MIN. GRADE OF C OR MAT 313 FOR LEVEL U WITH MIN. GRADE OF C OR MAT 375 FOR LEVEL U WITH MIN. GRADE OF C
-
3.00 Credits
Introduction to the study of matrices, linear systems, determinants, eigenvalues, and the geometry of linear operators. Topics from Euclidean n-space include linear transformations, linear independence, span, bases, inner product, and vector spaces. An introduction to structural proof techniques will be a part of the key concepts for the course.
Prerequisite:
MAT 212 FOR LEVEL U WITH MIN. GRADE OF C OR MAT 225 FOR LEVEL U WITH MIN. GRADE OF C
-
3.00 Credits
This is the second 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 may include using statistical inference to infer properties of a population, using regression analysis to estimate the relationship among variables, using machine learning to make predictions, and creating interactive data products.
Prerequisite:
MAT 219 FOR LEVEL U WITH MIN. GRADE OF C
-
3.00 Credits
Introduction to abstract algebraic structures and formal mathematical proof. Structures may include groups, rings, or fields.
Prerequisite:
MAT 225 FOR LEVEL U WITH MIN. GRADE OF C
-
3.00 Credits
Study of first order differential equations. Topics include modeling with differential equations, initial value problems, first and second order linear differential equations, systems of linear differential equations and numerical methods, as well as material chosen from the following topics: Laplace transforms, advanced numerical methods, and partial differential equations.
Prerequisite:
MAT 212 FOR LEVEL U WITH MIN. GRADE OF C
-
3.00 Credits
Study of construction of mathematical models to solve real world problems. Entire modeling process from construction of the model, fitting data to the model, analysis, and verification of the model covered. Both continuous and discrete models examined. Examples taken from a variety of disciplines. If prerequisite courses are not met instructor approval is required.
Prerequisite:
MAT 212 FOR LEVEL U WITH MIN. GRADE OF C OR MAT 318 FOR LEVEL U WITH MIN. GRADE OF C
-
3.00 Credits
Rigorous treatment of foundations of Euclidean geometry and an introduction to spherical and hyperbolic geometries. Topics may include transformational geometry, coordinate geometry, congruence, similarity and constructions. Also provides an historical development of attempts made through the centuries to clarify and expand upon the geometric axioms.
Prerequisite:
MAT 225 FOR LEVEL U WITH MIN. GRADE OF D
-
4.00 Credits
Course topics will include basic probability rules, conditional probability and independence, Bayes rule, discrete and continuous random variables, joint distributions, expectation and variance, probability distributions to include binomial, geometric, hypergeometric, Poisson, Gaussian, exponential, lognormal, t, F, and Chi-square, correlation and covariance, Central Limit Theorem and sampling distributions, simple linear regression, and inference procedures for means and proportions. A statistical software package will be used throughout the course. This class is NOT OPEN to students who have successfully passed MAT 217.
Prerequisite:
MAT 211 FOR LEVEL U WITH MIN. GRADE OF D
-
1.00 - 3.00 Credits
Opportunity to offer courses in areas of departmental major interest not covered by the regular courses.
-
3.00 Credits
Contact the department for further information on internships.
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Privacy Statement
|
Terms of Use
|
Institutional Membership Information
|
About AcademyOne
Copyright 2006 - 2024 AcademyOne, Inc.
|
|
|