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Ding, J.; Rhee, N. H. – College Mathematics Journal, 2013
A stochastic matrix is a square matrix with nonnegative entries and row sums 1. The simplest example is a permutation matrix, whose rows permute the rows of an identity matrix. A permutation matrix and its inverse are both stochastic. We prove the converse, that is, if a matrix and its inverse are both stochastic, then it is a permutation matrix.
Descriptors: Mathematics Instruction, College Mathematics, Matrices, Mathematical Concepts
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James, David; Botteron, Cynthia – College Mathematics Journal, 2013
A certain weighted average of the rows (and columns) of a nonnegative matrix yields a surprisingly simple, heuristical approximation to its singular vectors. There are correspondingly good approximations to the singular values. Such rules of thumb provide an intuitive interpretation of the singular vectors that helps explain why the SVD is so…
Descriptors: Mathematics Instruction, College Mathematics, Mathematical Concepts, Matrices
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Trenkler, Gotz; Trenkler, Dietrich – College Mathematics Journal, 2012
The numerical range, easy to understand but often tedious to compute, provides useful information about a matrix. Here we describe the numerical range of a 3 x 3 magic square. Applying our results to one of the most famous of those squares, the Luoshu, it turns out that its numerical range is a piece of cake--almost.
Descriptors: Problem Solving, Mathematical Concepts, Computation, Matrices
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Taalman, L.; Tongen, A.; Warren, B.; Wyrick-Flax, F.; Yoon, I. – College Mathematics Journal, 2013
This paper introduces a new matrix tool for the sowing game Tchoukaillon, which establishes a relationship between board vectors and move vectors that does not depend on actually playing the game. This allows for simpler proofs than currently appear in the literature for two key theorems, as well as a new method for constructing move vectors.We…
Descriptors: College Mathematics, Mathematics Instruction, Validity, Educational Games
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Stewart, Ian – College Mathematics Journal, 2012
Martin Gardner wrote about a coin-flipping trick, performed by a blindfolded magician. The paper analyses this trick, and compares it with a similar trick using three cups flipped in pairs. Several different methods of analysis are discussed, including a graphical analysis of the state space and a representation in terms of a matrix. These methods…
Descriptors: Mathematics, Visual Aids, Matrices, Comparative Analysis
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Fontaine, Anne; Hurley, Susan – College Mathematics Journal, 2011
This student research project explores the properties of a family of matrices of zeros and ones that arises from the study of the diagonal lengths in a regular polygon. There is one family for each n greater than 2. A series of exercises guides the student to discover the eigenvalues and eigenvectors of the matrices, which leads in turn to…
Descriptors: Student Research, Mathematics Instruction, College Mathematics, Mathematical Concepts
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Cheteyan, Leslie A.; Hengeveld, Stewart; Jones, Michael A. – College Mathematics Journal, 2011
In this paper, we review the rules and game board for "Chutes and Ladders", define a Markov chain to model the game regardless of the spinner range, and describe how properties of Markov chains are used to determine that an optimal spinner range of 15 minimizes the expected number of turns for a player to complete the game. Because the Markov…
Descriptors: Markov Processes, Mathematics Instruction, Games, Teaching Methods
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Leggett, Deanna; Perry, John; Torrence, Eve – College Mathematics Journal, 2011
Dodgson's method of computing determinants is attractive, but fails if an interior entry of an intermediate matrix is zero. This paper reviews Dodgson's method and introduces a generalization, the double-crossing method, that provides a workaround for many interesting cases.
Descriptors: Matrices, Teaching Methods, Mathematics Instruction, Problem Solving
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Rice, Adrian; Torrence, Eve – College Mathematics Journal, 2007
Charles Dodgson (Lewis Carroll) discovered a "curious" method for computing determinants. It is an iterative process that uses determinants of 2 x 2 submatrices of a matrix to obtain a smaller matrix. When the process ends, the result is the determinant of the original matrix. This article discusses both the algorithm and what may have led Dodgson…
Descriptors: Matrices, Problem Solving, Computation, Mathematical Concepts
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Kalman, Dan – College Mathematics Journal, 1984
Two methods for solving matrix equations are discussed. Both operate entirely on a matrix level. (MNS)
Descriptors: Algebra, College Mathematics, Higher Education, Mathematics
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Spivey, Michael – College Mathematics Journal, 2006
We use the sum property for determinants of matrices to give a three-stage proof of an identity involving Fibonacci numbers. Cassini's and d'Ocagne's Fibonacci identities are obtained at the ends of stages one and two, respectively. Catalan's Fibonacci identity is also a special case.
Descriptors: Mathematical Concepts, Matrices, College Mathematics, Validity
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Arganbright, Deane E. – College Mathematics Journal, 1984
How to use the electronic spreadsheet (e.g., VisiCalc) creatively is discussed, with computer printouts for a number of algorithms. (MNS)
Descriptors: Algorithms, College Mathematics, Computer Oriented Programs, Computer Programs
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Marcus, Marvin – College Mathematics Journal, 1990
Presents two papers commenting on previous published articles. Discusses formulas related to the determinants of sums and tests the formulas using some examples. Provides three special cases of the determinants of sums. (YP)
Descriptors: Algebra, College Mathematics, Computation, Higher Education
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Tucker, Alan – College Mathematics Journal, 1993
Discusses the theoretical and practical importance of linear algebra. Presents a brief history of linear algebra and matrix theory and describes the place of linear algebra in the undergraduate curriculum. (MDH)
Descriptors: College Mathematics, Higher Education, Mathematical Applications, Mathematics Curriculum
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Caulfield, Michael; And Others – College Mathematics Journal, 1986
The problem of controlling the grizzly bear population at Yellowstone is described. The results are presented in graphical form and discussed. A computer program is included. (MNS)
Descriptors: College Mathematics, Computer Software, Graphs, Higher Education
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