Resources for ENC students, staff, and faculty.
Differential Equations with Boundary-Value Problems
Call Number: QA371 .Z55 2008
Publication Date: 2008-05-13
7th Edition strikes a balance between the analytical, qualitative, and quantitative approaches to the study of differential equations. This proven and accessible text speaks to beginning engineering and math students through a wealth of pedagogical aids, including an abundance of examples, explanations, "Remarks" boxes, definitions, and group projects. Using a straightforward, readable, and helpful style, this book provides a thorough treatment of boundary-value problems and partial differential equations.
Call Number: Q325.5 .B347 2012
Publication Date: 2006-08-04
A visually intuitive approach to statistical data analysis Visual Statistics brings the most complex and advanced statistical methods within reach of those with little statistical training by using animated graphics of the data. The book provides users with the opportunity to view the graphics in a dynamic way by illustrating how to analyze statistical data and explore the concepts of visual statistics and is also ideal as a reference/self-study guide for engineers, scientists, and mathematicians. With contributions by highly regarded professionals in the field, Visual Statistics not only improves a student's understanding of statistics, but also builds confidence to overcome problems that may have previously been intimidating.
Basic Data Analysis for Time Series with R
Call Number: QA280 .D475 2014
Publication Date: 2014-07-08
Written at a readily accessible level, Basic Data Analysis for Time Series with R emphasizes the mathematical importance of collaborative analysis of data used to collect increments of time or space. Balancing a theoretical and practical approach to analyzing data within the context of serial correlation, the book presents a coherent and systematic regression-based approach to model selection. The book illustrates these principles of model selection and model building through the use of information criteria, cross validation, hypothesis tests, and confidence intervals.
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This multi-disciplinary database provides full text for thousands of journals, including full text for many peer-reviewd titles and PDF backfiles to 1886. Some useful subjects in this database include business, marketing management and economics.
This electronic publication offers access to a carefully maintained and easily searchable database of reviews, abstracts and bibliographic information for much of the mathematical sciences literature. Over 100,000 new items are added each year, most of them classified according to the Mathematics Subject Classification. MathSciNet® contains over 2.8 million items and over 1.6 million direct links to original articles. Bibliographic data from retrodigitized articles dates back to the early 1800s. Reference lists are collected and matched internally from approximately 500 journals, and citation data for journals, authors, articles and reviews is provided.
- Science Citation Index
The Science Citation Index (part of Web of Science) provides access to current and retrospective bibliographic information, author abstracts, and cited references found in approximately 5,900 of the world's leading scholarly science and technical journals covering more than 150 disciplines. AFIT access to partial-full text only.
Did you know that we also link our full-text databases through Google Scholar? If you search from any campus computer or authenticate through VPN, Google Scholar will direct you to sources from the D'Azzo Research Library.
arXiv is a highly-automated electronic archive and distribution server for research articles. Covered areas include physics, mathematics, computer science, nonlinear sciences, quantitative biology and statistics. Maintained and operated by the Cornell University Library , arXiv is an openly accessible, moderated repository for scholarly articles in specific scientific disciplines. Material submitted to arXiv is expected to be of interest, relevance, and value to those disciplines. arXiv reserves the right to reject or reclassify any submission.
- American Mathematical Society (AMS)
The American Mathematical Society (AMS) is an association of professional mathematicians dedicated to the interests of mathematical research and scholarship, and serves the national and international community through its publications, meetings, advocacy and other programs.
- Mathematical Association of America (MAA)
The Mathematical Association of America is the largest professional society that focuses on mathematics accessible at the undergraduate level. MAA is the leading professional association in collegiate mathematics, the preeminent publisher of expository mathematics, the primary source of professional development programs for faculty, and the number one provider of resources for teaching and learning.
- Society for Industrial and Applied Mathematics (SIAM)
SIAM exists to ensure the strongest interactions between mathematics and other scientific and technological communities through membership activities, publication of journals and books, and conferences.
- American Statistical Association (ASA)
The worlds largest community of statistians, ASA promotes excellence in the development, application, and dissemination of statistical science through meetings, publications, membership services, education, accreditation, and advocacy.
- International Association Statistical Computing (IASC)
A division of the International Statitistician Institute (ISI), the IASC focuses on computational statistics, statistical software, exploratory data analysis, data mining, pattern recognition, statistical graphics and data visualisation, statistical data bases, and related fields.
Need help? Set up an appointment with the ENC library liaison for literature searching assistance.
AMPL is a comprehensive and powerful algebraic modeling language for linear and nonlinear optimization problems, in discrete or continuous variables.
CPLEX's mathematical optimization technology enables better decision-making for efficient resource utilization.
MATLAB is a programming environment for algorithm development, data analysis, visualization, and numerical computation. Using MATLAB, you can solve technical computing problems faster than with traditional programming languages, such as C, C++, and Fortran.
Mathematica is renowned as the world's ultimate application for computations.