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Matrices and Matrix Operations with TI-Nspire™ CAS Forest W. Arnold June 2020 A Typeset in LT X. E Copyright © 2020 Forest W. Arnold This work is licensed under the Creative Commons Attribution-Noncommercial-Share Alike4.0InternationalLicense. Toviewacopyofthislicense,visithttp://creativecommons. org/licenses/by-nc-sa/4.0/legalcode/orsendaletter to Creative Commons, 171SecondStreet, Suite 300, San Francisco, California, 94105, USA. You can use, print, duplicate, share this work as much as you want. You can base your own work on it and reuse parts if you keep the license the same. Trademarks TI-Nspire is a registered trademark of Texas Instruments, Inc. Attribution MostoftheexamplesinthisarticlearefromAFirstCourseinLinearAlgebraanOpen Text by Lyrix Learning, base textbook version 2017 - revision A, by K. Kuttler. The text is licensed under the Creative Commons License (CC BY) and is available for download at the link https://lyryx.com/first-course-linear-algebra/. 1 Introduction Thearticle Systems of Equations with TI-Nspire™ CAS: Matrices and Gaussian Elim- ination described how to represent and solve systems of linear equations with matrices and elementary row operations. By defining arithmetic and algebraic operations with matrices, applications of matrices can be expanded to include more than simply solving linear systems. Thisarticle describes and demonstrates how to use TI-Nspire’s builtin matrix functions to • add and subtract matrices, • multiply matrices by scalars, • multiply matrices, • transpose matrices, • find matrix inverses, and • use matrix equations. TheTI-Nspire examples in this article require the CAS version of TI-Nspire. 2 Matrices and Vectors In TI-Nspire CAS, a matrix is a rectangular array of expressions (usually numbers) with m rows and n columns. The dimension (size) of a matrix is denoted as m×n. Whenstating the dimension of a matrix, m, the number of rows is always stated first. Anexampleofa3×4matrixis a a a a 11 12 13 14 a a a a (1) 21 22 23 24 a a a a 31 32 33 34 Avector is either a matrix with one row and multiple columns (a row vector) or a matrix with multiple rows and a single column (a column vector). An example of a rowvector is rv1 rv2 rv3 rv4 (2) and an example of a column vector is cv1 cv2 (3) cv3 1
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