Applied Finite Mathematics covers topics including linear equations, matrices, linear programming, the mathematics of finance, sets and counting, probability, Markov chains, and game theory. Endorsed by CollegeOpenTextbooks.org.
This applied mathematics textbook covers Matrices and Pathways, Statistics and Probability, Finance, Cyclic, Recursive and Fractal Patterns, Vectors, and Design. The approach used is primarily data driven, using numerical and geometrical problem-solving techniques.
The main objective of this lesson is to illustrate an important application of mathematics in practical life -- namely in art. Most of the pictures selected for this lesson are visible on the walls of Al-Hambra – Granada (Spain), which is one of the most important landmarks in the Islamic civilization. There are three educational goals for this lesson: (1) establishing the concept of isometries; (2) giving real-life examples of groups; (3) demonstrating the importance of matrices and their applications. As background for this lesson, students just need some familiarity with the concept of a group and a limited knowledge about matrices and the inverse of a non-singular matrix.
The power of graphics should not the underestimated. They can express information clearly and simply. This unit will help you to assess which style of graphic to use in different situations.
This course is is a collection of resources on OER Commons curated for Adult Education instructors and students to show the integration of math into the Information Technology Career Sector. Students will analyze and practice specific skills related to being in IT as well as develop math skills. Modules in this curriculum guide can be studied in any particular order as one does not necessarily build upon the other. Each includes the idea of building mathematical and logic skills required for programming and other IT related careers.
This Intermediate Algebra textbook was developed with consideration of neuroscience principles about learning. It is organized around the concepts of 'solving' and 'graphing'. The problem sets incorporate distributed and mixed practice to promote long term memory formation for the concepts and procedures involved in each section.
Matlab es un lenguaje de programación matemática que sirve para realizar cálculos algebraicos, así como también para programar y ejecutar simulaciones, modelos y aplicaciones de ingeniería, basándose fundamentalmente en la utilización de matrices. Matlab es un entorno computacional aplicado a varias áreas de la ciencia moderna como:
- Matemáticas, estadísticas y optimización.
- Diseño y análisis de sistemas de control.
- Procesamiento de señales espectrales en comunicaciones.
- Procesamiento de imágenes y visión computacional.
- Medición y verificación de bases de datos.
- Finanzas computacionales.
- Biología computacional.
- Generación de códigos de programación C++.
- Desarrollo de aplicativos computacionales.
- Conectividad de bases de datos.
- Simulación gráfica de imágenes satelitáles.
Sal checks whether the commutative property applies for matrix multiplication. In other words, he checks whether for any two matrices A and B, A*B=B*A (the answer is NO, by the way). Created by Sal Khan.
The Linear Algebra is a branch Mathematics that studies systems of linear equations and the property of matrices. It is one of the sectors with the vast and varied applications. The matrix calculus, vector calculus, linear applications and the design values and eigenvectors of an endomorphism have wide application in various branches of knowledge, particularly in the computer industry. Moreover, their concepts and developments lend themselves to multiple interpretations and the most diverse uses
This 27-minute video lesson provides an example using the orthogonal change-of-basis matrix to find the transformation matrix. [Linear Algebra playlist: Lesson 128 of 143]
This 17-minute video lesson shows how to express a projection on to a line as a Matrix Vector prod. [Linear Algebra playlist: Lesson 61 of 143]
This 12-minute video lesson provides an introduction to the null space of a matrix and shows that the null space of a matrix is a valid subspace. [Linear Algebra playlist: Lesson 34 of 143]
This 18-minute video lesson shows how to solve a system of linear equations by putting an augmented matrix into reduced row echelon form. [Linear Algebra playlist: Lesson 30 of 143]
This 12-minute video lesson provides another example of solving a system of linear equations by putting an augmented matrix into reduced row echelon form. [Linear Algebra playlist: Lesson 32 of 143]
This 13-minute video lesson shows how to calculate the null space of a matrix. [Linear Algebra playlist: Lesson 35 of 143]
This 12-minute video lesson discusses how to understand how the null space of a matrix relates to the linear independence of its column vectors. [Linear Algebra playlist: Lesson 36 of 143]
This 11-minute video lesson shows that orthogonal matrices preserve angles and lengths. [Linear Algebra playlist: Lesson 129 of 143]