Linear Algebra and Its Applications (5th Edition)

Published by Pearson
ISBN 10: 032198238X
ISBN 13: 978-0-32198-238-4

Chapter 1 - Linear Equations in Linear Algebra - 1.10 Exercises - Page 88: 10

Answer

(a) $\left[\begin{array}{ll}0.94 & 0.04 \\ 0.06 & 0.96\end{array}\right] \mathbf{x}_{k}=\mathbf{x}_{k+1}$ (b) $\left[\begin{array}{l}8920800 \\ 1879200\end{array}\right]$

Work Step by Step

This solution appears in both the sections for the 4 th and 5 th editions of Lay's Linear Algebra and Its Applications since the only difference between the questions is that the years considered in the 4 th edition are 2010 and 2012 while in the 5 th edition they are 2015 and 2017 . I write this for the 5 th edition, thus if you're using the 4 th, just substitute the correct years in your work. It doesn't actually affect the final answer though since in both cases the difference of the years is 2 Let $p_{c}$ be the population of the city (in a given year) and $p_{s}$ be the population of the suburbs (in the same year). The first sentence of the exercise statement says us that the populations $p_{c}^{\prime}$ and $p_{s}^{\prime}$ for the next year will be \[ \begin{array}{l} 0.94 p_{c}+0.04 p_{s}=p_{c}^{\prime} \\ 0.06 p_{c}+0.96 p_{s}=p_{s}^{\prime} \end{array} \] we used the fact that if $6 \%$ (resp. $4 \%$ ) moves then $94 \%$ (resp. $96 \%$ ) must stay put. We will sum this up in the matrix equation \[ \left[\begin{array}{ll} 0.94 & 0.04 \\ 0.06 & 0.96 \end{array}\right]\left[\begin{array}{l} p_{c} \\ p_{s} \end{array}\right]=\left[\begin{array}{l} p_{c}^{\prime} \\ p_{s}^{\prime} \end{array}\right] \] Written in the usual difference equation notation this is \[ \left[\begin{array}{ll} 0.94 & 0.04 \\ 0.06 & 0.96 \end{array}\right] \mathbf{x}_{k}=\mathbf{x}_{k+1} \] Now put $\mathbf{x}_{0}=\left[\begin{array}{c}\text { population in the city in } 2015 \\ \text { population in the suburbs in } 2015\end{array}\right]$ be the $2 \times 1$ population vector for 2015 . Then \[ \mathbf{x}_{1}=\left[\begin{array}{ll} 0.94 & 0.04 \\ 0.06 & 0.96 \end{array}\right] \mathbf{x}_{0} \]
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