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Online Notes / Linear Algebra / Determinants / Cramer's Rule
Linear Algebra

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In this section we’re going to come back and take one more look at solving systems of equations.  In this section we’re actually going to be able to get a general solution to certain systems of equations.  It won’t work on all systems of equations and as we’ll see if the system is too large it will probably be quicker to use one of the other methods that we’ve got for solving systems of equations.

 

So, let’s jump into the method.

 

Theorem 1 Suppose that A is an  invertible matrix.  Then the solution to the system  is given by,

                                    

where  is the matrix found by replacing the ith column of A with b.

 

Proof : The proof to this is actually pretty simple.  First, because we know that A is invertible then we know that the inverse exists and that .  We also know that the solution to the system can be given by,

 

 

 

From the section on cofactors we know how to define the inverse in terms of the adjoint of A.  Using this gives us,

 

 

 

 

Recall that  is the cofactor of .  Also note that the subscripts on the cofactors above appear to be backwards but they are correctly placed.  Recall that we get the adjoint by first forming a matrix with  in the ith row and jth column and then taking the transpose to get the adjoint.

 

Now, multiply out the matrices to get,

 

 

 

The entry in the ith row of x, which is  in the solution, is

 

 

 

Next let’s define,

 

 

 

So,  is the matrix we get by replacing the ith column of A with b.  Now, if we were to compute the determinate of  by expanding along the ith column the products would be one of the  ’s times the appropriate cofactor.  Notice however that since the only difference between  and A is the ith column and so the cofactors of we get by expanding  along the ith column will be exactly the same as the cofactors we would get by expanding A along the ith column.

 

Therefore, the determinant of  is given be,

 

 

where  is the cofactor of  from the matrix A.  Note however that this is exactly the numerator of  and so we have,

 

 

as we wanted to prove.

Pf_Box

 

Let’s work a quick example to illustrate the method.

 

Example 1  Use Cramer’s Rule to determine the solution to the following system of equations.

                                                         

Solution

First let’s put the system into matrix form and verify that the coefficient matrix is invertible.

                                                    

 

                                                          

 

So, the coefficient matrix is invertible and Cramer’s Rule can be used on the system.  We’ll also need det(A) in a bit so it’s good that we now have it.  Let’s now write down the formulas for the solution to this system.

                           

where  is the matrix formed by replacing the 1st column of A with b,  is the matrix formed by replacing the 2nd column of A with b, and  is the matrix formed by replacing the 3rd column of A with b.

 

We’ll leave it to you to verify the following determinants.

                                                

 

The solution to the system is then,

                              

 

Now, the solution to this system had some somewhat messy solutions and that would have made the row reduction method prone to mistake.  However, since this solution required us to compute 4 determinants as you can see if your system gets too large this would be a very time consuming method to use.  For example a system with 5 equations and 5 unknowns would require us to compute 6  determinants.  At that point, regardless of how messy the final answers are there is a good chance that the row reduction method would be easier.


Online Notes / Linear Algebra / Determinants / Cramer's Rule

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