/*! This file is auto-generated */ .wp-block-button__link{color:#fff;background-color:#32373c;border-radius:9999px;box-shadow:none;text-decoration:none;padding:calc(.667em + 2px) calc(1.333em + 2px);font-size:1.125em}.wp-block-file__button{background:#32373c;color:#fff;text-decoration:none} Problem 1 Determine whether each of the fo... [FREE SOLUTION] | 91Ó°ÊÓ

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Determine whether each of the following equations is linear: (a) \(5 x+7 y-8 y z=16\) (b) \(x+\pi y+e z=\log 5\) (c) \(3 x+k y-8 z=16\)

Short Answer

Expert verified
Equation (a) is nonlinear due to the product of variables in the term "-8yz". Equations (b) and (c) are linear, as all variables have a degree of 1 and there are no products of variables.

Step by step solution

01

Analyze equation (a)

For the equation (a) \(5x + 7y - 8yz = 16\), examine each term. We see that all the variables 'x' and 'y' have a degree of 1. However, in the term "-8yz", the variables 'y' and 'z' are multiplied together. This makes the equation nonlinear.
02

Analyze equation (b)

For the equation (b) \(x + \pi y + e z = \log 5\), examine each term. We see that all the variables 'x', 'y', and 'z' have a degree of 1. The constants \(\pi\), \(e\), and \(\log 5\) do not affect the linearity of the equation. Since there are no products of variables, equation (b) is linear.
03

Analyze equation (c)

For the equation (c) \(3x + ky - 8z = 16\), examine each term. We see that all the variables 'x', 'y', and 'z' have a degree of 1. The constant 'k' and '16' do not affect the linearity of the equation. Since there are no products of variables, equation (c) is linear. Therefore, equation (a) is nonlinear, and equations (b) and (c) are linear.

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Key Concepts

These are the key concepts you need to understand to accurately answer the question.

nonlinear equations
When dealing with equations, it's important to distinguish between linear and nonlinear equations.
Nonlinear equations do not have a constant rate of change and can have more complex structures.
In the context of algebra, a nonlinear equation is one where there's at least one term that involves the product of variables or a variable raised to a power greater than 1.
For example, in the equation \(5x + 7y - 8yz = 16\), the term \(-8yz\) shows multiplication between 'y' and 'z'.
This term makes the equation nonlinear because it involves a product of two variables. Nonlinear equations can involve curves instead of straight lines when plotted on a graph.
They can be more complex to solve and analyze because their behavior can change depending on the values of the variables.
degree of a polynomial
The degree of a polynomial gives us a sense of how the output of a polynomial function changes as the input changes.
It is the highest power of any variable in the polynomial. For linear equations, the degree is typically 1 for all terms that contain variables.
Each variable in a polynomial term is raised to a certain power.
  • The degree of a term is the sum of the powers of all variables in that term.
  • For example, in the equation \(5x + 7y - 8z = 16\), all terms have variables with a degree of 1.
In the context of the equation \(-8yz = 16\), the term \(-8yz\) is actually a degree 2 term because 'y' and 'z' are multiplied (and each is to the power of 1, giving a total power of 2).
Understanding the degree of a polynomial is crucial to identifying the nature of equations in algebra.
It helps determine whether an equation is linear or nonlinear and influences the shape of the graph when plotted.
products of variables
Products of variables occur when multiple variables are multiplied together in an equation.
This usually results in a more complex equation and often indicates nonlinearity.
Products of variables can elevate the degree of a term, making it greater than 1.
  • This is seen in terms like \(-8yz\) from the equation \(5x + 7y - 8yz = 16\), where 'y' and 'z' are multiplied.
  • When variables are multiplied, they alter the straightforward relationship seen in linear equations.
The multiplication of variables can lead to quadratic or higher degree equations, depending on how many variables and to what powers they are raised.
Understanding this concept is pivotal in algebra, as it affects how equations are solved and analyzed.
It helps to identify whether an equation will yield a straight line or a curve when graphing its solutions.

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Most popular questions from this chapter

Let \(A\) be the matrix in Problem 3.41. Find \(X_{1}, X_{2}, X_{3}\), where \(X_{i}\) is the solution of \(A X=B_{i}\) for (a) \(B_{1}=(1,1,1)\), (b) \(B_{2}=B_{1}+X_{1}\), (c) \(B_{3}=B_{2}+X_{2}\) (a) Find \(L^{-1} B_{1}\) by applying the row operations (1), (2), and then (3) in Problem \(3.41\) to \(B_{1}\) : $$ B_{1}=\left[\begin{array}{l} 1 \\ 1 \\ 1 \end{array}\right] \stackrel{(1) \operatorname{and}(2)}{\longrightarrow}\left[\begin{array}{r} 1 \\ -1 \\ 4 \end{array}\right] \longrightarrow \quad(3) \quad\left[\begin{array}{r} 1 \\ -1 \\ 8 \end{array}\right] $$ Solve \(U X=B\) for \(B=(1,-1,8)\) by back-substitution to obtain \(X_{1}=(-25,9,8)\) (b) First find \(B_{2}=B_{1}+X_{1}=(1,1,1)+(-25,9,8)=(-24,10,9)\). Then as above $$ B_{2}=[-24,10,9]^{T} \stackrel{(1) \operatorname{and}(2)}{\longrightarrow}[-24,58,-63]^{T} \longrightarrow \stackrel{(3)}{\longrightarrow}[-24,58,-295]^{T} $$ Solve \(U X=B\) for \(B=(-24,58,-295)\) by back-substitution to obtain \(X_{2}=(943,-353,-295)\) (c) First find \(B_{3}=B_{2}+X_{2}=(-24,10,9)+(943,-353,-295)=(919,-343,-286)\). Then, as above $$ B_{3}=[943,-353,-295]^{T} \stackrel{(1) \text { and }(2)}{\longrightarrow}[919,-2181,2671]^{T} \longrightarrow^{(3)} \longrightarrow[919,-2181,11395]^{T} $$ Solve \(U X=B\) for \(B=(919,-2181,11395)\) by back-substitution to obtain $$ X_{3}=(-37628,13576,11395) $$

Consider the system $$\begin{array}{c} x+a y=4 \\ a x+9 y=b \end{array}$$ (a) For which values of \(a\) does the system have a unique solution? (b) Find those pairs of values \((a, b)\) for which the system has more than one solution.

Reduce each of the following matrices to echelon form and then to row canonical form: (a) \(\left[\begin{array}{rrrrrr}1 & 2 & 1 & 2 & 1 & 2 \\ 2 & 4 & 3 & 5 & 5 & 7 \\ 3 & 6 & 4 & 9 & 10 & 11 \\ 1 & 2 & 4 & 3 & 6 & 9\end{array}\right]\) (b) \(\left[\begin{array}{rrrr}0 & 1 & 2 & 3 \\ 0 & 3 & 8 & 12 \\ 0 & 0 & 4 & 6 \\ 0 & 2 & 7 & 10\end{array}\right]\) (c) \(\left[\begin{array}{rrrr}1 & 3 & 1 & 3 \\ 2 & 8 & 5 & 10 \\ 1 & 7 & 7 & 11 \\ 3 & 11 & 7 & 15\end{array}\right]\)

Find the dimension and a basis for the general solution \(W\) of the following homogeneous system using matrix notation: $$ \begin{array}{r} x_{1}+2 x_{2}+3 x_{3}-2 x_{4}+4 x_{5}=0 \\ 2 x_{1}+4 x_{2}+8 x_{3}+x_{4}+9 x_{5}=0 \\ 3 x_{1}+6 x_{2}+13 x_{3}+4 x_{4}+14 x_{5}=0 \end{array} $$ Show how the basis gives the parametric form of the general solution of the system. When a system is homogeneous, we represent the system by its coefficient matrix \(A\) rather than by its augmented matrix \(M\), because the last column of the augmented matrix \(M\) is a zero column, and it will remain a zero column during any row-reduction process. Reduce the coefficient matrix \(A\) to echelon form, obtaining $$ A=\left[\begin{array}{rrrrr} 1 & 2 & 3 & -2 & 4 \\ 2 & 4 & 8 & 1 & 9 \\ 3 & 6 & 13 & 4 & 14 \end{array}\right] \sim\left[\begin{array}{rrrrr} 1 & 2 & 3 & -2 & 4 \\ 0 & 0 & 2 & 5 & 1 \\ 0 & 0 & 4 & 10 & 2 \end{array}\right] \sim\left[\begin{array}{rrrrr} 1 & 2 & 3 & -2 & 4 \\ 0 & 0 & 2 & 5 & 1 \end{array}\right] $$ (The third row of the second matrix is deleted, because it is a multiple of the second row and will result in a zero row.) We can now proceed in one of two ways. (a) Write down the corresponding homogeneous system in echelon form: $$ \begin{array}{r} x_{1}+2 x_{2}+3 x_{3}-2 x_{4}+4 x_{5}=0 \\ 2 x_{3}+5 x_{4}+x_{5}=0 \end{array} $$ The system in echelon form has three free variables, \(x_{2}, x_{4}, x_{5}\), so \(\operatorname{dim} W=3\). A basis \(\left[u_{1}, u_{2}, u_{3}\right]\) for \(W\) may be obtained as follows: (1) Set \(x_{2}=1, x_{4}=0, x_{5}=0\). Back-substitution yields \(x_{3}=0\), and then \(x_{1}=-2\). Thus, \(u_{1}=(-2,1,0,0,0)\) (2) Set \(x_{2}=0, x_{4}=1, x_{5}=0\). Back-substitution yields \(x_{3}=-\frac{5}{2}\), and then \(x_{1}=\frac{19}{2}\). Thus, \(u_{2}=\left(\frac{19}{2}, 0,-\frac{5}{2}, 1,0\right)\) (3) Set \(x_{2}=0, x_{4}=0, x_{5}=1\). Back-substitution yields \(x_{3}=-\frac{1}{2}\), and then \(x_{1}=-\frac{5}{2}\). Thus, \(u_{3}=\left(-\frac{5}{2}, 0,-\frac{1}{2}, 0,1\right)\) [One could avoid fractions in the basis by choosing \(x_{4}=2\) in (2) and \(x_{5}=2\) in (3), which yields multiples of \(u_{2}\) and \(u_{3}\).] The parametric form of the general solution is obtained from the following linear combination of the basis vectors using parameters \(a, b, c\) : $$ a u_{1}+b u_{2}+c u_{3}=\left(-2 a+\frac{19}{2} b-\frac{5}{2} c, a,-\frac{5}{2} b-\frac{1}{2} c, b, c\right) $$ (b) Reduce the echelon form of \(A\) to row canonical form: $$ A \sim\left[\begin{array}{ccccc} 1 & 2 & 3 & -2 & 4 \\ 0 & 0 & 1 & \frac{5}{2} & \frac{1}{2} \end{array}\right] \sim\left[\begin{array}{rrrrr} 1 & 2 & 3 & -\frac{19}{2} & \frac{5}{2} \\ 0 & 0 & 1 & \frac{5}{2} & \frac{1}{2} \end{array}\right] $$ Write down the corresponding free-variable solution: $$ \begin{aligned} &x_{1}=-2 x_{2}+\frac{19}{2} x_{4}-\frac{5}{2} x_{5} \\ &x_{3}=-\frac{5}{2} x_{4}-\frac{1}{2} x_{5} \end{aligned} $$ Using these equations for the pivot variables \(x_{1}\) and \(x_{3}\), repeat the above process to obtain a basis \(\left[u_{1}, u_{2}, u_{3}\right]\) for \(W\). That is, set \(x_{2}=1, x_{4}=0, x_{5}=0\) to get \(u_{1} ;\) set \(x_{2}=0, x_{4}=1, x_{5}=0\) to get \(u_{2}\); and set \(x_{2}=0\), \(x_{4}=0, x_{5}=1\) to get \(u_{3}\).

Find the \(L U\) factorization of the matrix \(A=\left[\begin{array}{rrr}1 & 2 & 1 \\ 2 & 3 & 3 \\ -3 & -10 & 2\end{array}\right]\)

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