Why are linear equations usually written down as matrices?

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SUMMARY

Linear equations are often represented in matrix form for efficiency and clarity. The matrix representation allows for operations such as finding the inverse of a matrix to solve systems of equations, exemplified by the system 2x + y = 5 and x + 3y = 5, which can be expressed as Ax = b. Here, A is the coefficient matrix, and b is the result vector. Using matrices simplifies the notation and facilitates complex calculations involving multiple linear transformations.

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  • Understanding of linear equations and systems
  • Familiarity with matrix operations, including multiplication and inversion
  • Knowledge of vector notation and representation
  • Basic skills in algebraic manipulation
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  • Learn about the application of matrices in solving linear systems using the Gaussian elimination method
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japplepie
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I've been taught that for any system of linear equations, it has a corresponding matrix.

Why do people sometimes use systems of linear equations to describe something and other times matrices?

Is it all just a way of writing things down faster or are there things you could do to matrices that you couldn't do to linear equations?
 
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japplepie said:
I've been taught that for any system of linear equations, it has a corresponding matrix.

Why do people sometimes use systems of linear equations to describe something and other times matrices?

Is it all just a way of writing things down faster or are there things you could do to matrices that you couldn't do to linear equations?
Mostly matrices are a shorthand way of writing a system of linear equations, but there is one other advantage for certain systems : the ability to use a matrix inverse to solve the system.

For example, suppose we have this system:
2x + y = 5
x + 3y = 5

This system can be written in matrix form as:
##\begin{bmatrix} 2 & 1 \\ 1 & 3 \end{bmatrix}\begin{bmatrix} x \\ y\end{bmatrix} = \begin{bmatrix} 5 \\5 \end{bmatrix}##
Symbolically, the system is Ax = b, where A is the matrix of coefficients on the left, and b is the column vector whose entries are 5 and 5. (x is the column vector of variables x and y.)

Because I cooked this example up, I know that A has an inverse; namely ##A^{-1} = \frac 1 5 \begin{bmatrix} 3 & -1 \\ -1 & 2 \end{bmatrix}##
If I apply this inverse to both sides of Ax = b, I get ##A^{-1}Ax = A^{-1}b = \frac 1 5 \begin{bmatrix} 3 & -1 \\ -1 & 2 \end{bmatrix} \begin{bmatrix} 5 \\5 \end{bmatrix}##
##= \begin{bmatrix} 2 \\1 \end{bmatrix}##

From this I see that x = 2 and y = 1. You can check that this is a solution by substituting these values in the system of equations.
 
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Mark44 said:
Mostly matrices are a shorthand way of writing a system of linear equations, but there is one other advantage for certain systems : the ability to use a matrix inverse to solve the system.

For example, suppose we have this system:
2x + y = 5
x + 3y = 5

This system can be written in matrix form as:
##\begin{bmatrix} 2 & 1 \\ 1 & 3 \end{bmatrix}\begin{bmatrix} x \\ y\end{bmatrix} = \begin{bmatrix} 5 \\5 \end{bmatrix}##
Symbolically, the system is Ax = b, where A is the matrix of coefficients on the left, and b is the column vector whose entries are 5 and 5. (x is the column vector of variables x and y.)

Because I cooked this example up, I know that A has an inverse; namely ##A^{-1} = \frac 1 5 \begin{bmatrix} 3 & -1 \\ -1 & 2 \end{bmatrix}##
If I apply this inverse to both sides of Ax = b, I get ##A^{-1}Ax = A^{-1}b = \frac 1 5 \begin{bmatrix} 3 & -1 \\ -1 & 2 \end{bmatrix} \begin{bmatrix} 5 \\5 \end{bmatrix}##
##= \begin{bmatrix} 2 \\1 \end{bmatrix}##

From this I see that x = 2 and y = 1. You can check that this is a solution by substituting these values in the system of equations.
I see, thank you very much!
 
Essentially, matrices allow you to write any system of linear equations as the single equation "Ax= b", the simplest form.
 
The shorthand notation provided by the matrix is very beneficial. Keeping track of the variables that the matrix operates on often clutters up the calculations. If you compose a sequence of linear operations ( E = A * B * C * D ), you can do the matrix manipulations easily. If you try to name and keep track of all the intermediate values, it is just an unnecessary mess. ( x2 = Dx1; x3 = Cx2; x4 = Bx3; x5 = Ax4; so x5 = E x1 )
 

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