SlideShare a Scribd company logo
1 of 106
Systems of Linear Equations
Systems of Linear Equations
We need one piece of information to solve for one
unknown quantity.
Systems of Linear Equations
We need one piece of information to solve for one
unknown quantity. If 2 hamburgers cost 4 dollars and
x is the cost of a hamburger, then 2x = 4 or x = $2.
Systems of Linear Equations
We need one piece of information to solve for one
unknown quantity. If 2 hamburgers cost 4 dollars and
x is the cost of a hamburger, then 2x = 4 or x = $2.
If there are two unknowns x and y, we need two
pieces of information to solve them.
Systems of Linear Equations
We need one piece of information to solve for one
unknown quantity. If 2 hamburgers cost 4 dollars and
x is the cost of a hamburger, then 2x = 4 or x = $2.
If there are two unknowns x and y, we need two
pieces of information to solve them.
Example A. Let x = cost of a hamburger,
y = cost of an order of fries. If two hamburgers and
an order of fries cost $7, and one hamburger and one
order of fries cost $5. What is the price of each?
Systems of Linear Equations
We need one piece of information to solve for one
unknown quantity. If 2 hamburgers cost 4 dollars and
x is the cost of a hamburger, then 2x = 4 or x = $2.
If there are two unknowns x and y, we need two
pieces of information to solve them.
Example A. Let x = cost of a hamburger,
y = cost of an order of fries. If two hamburgers and
an order of fries cost $7, and one hamburger and one
order of fries cost $5. What is the price of each?
We translate this information into two equations:
Systems of Linear Equations
We need one piece of information to solve for one
unknown quantity. If 2 hamburgers cost 4 dollars and
x is the cost of a hamburger, then 2x = 4 or x = $2.
If there are two unknowns x and y, we need two
pieces of information to solve them.
Example A. Let x = cost of a hamburger,
y = cost of an order of fries. If two hamburgers and
an order of fries cost $7, and one hamburger and one
order of fries cost $5. What is the price of each?
2x + y = 7
We translate this information into two equations:
Systems of Linear Equations
We need one piece of information to solve for one
unknown quantity. If 2 hamburgers cost 4 dollars and
x is the cost of a hamburger, then 2x = 4 or x = $2.
If there are two unknowns x and y, we need two
pieces of information to solve them.
Example A. Let x = cost of a hamburger,
y = cost of an order of fries. If two hamburgers and
an order of fries cost $7, and one hamburger and one
order of fries cost $5. What is the price of each?
2x + y = 7
x + y = 5
We translate this information into two equations:
Systems of Linear Equations
We need one piece of information to solve for one
unknown quantity. If 2 hamburgers cost 4 dollars and
x is the cost of a hamburger, then 2x = 4 or x = $2.
If there are two unknowns x and y, we need two
pieces of information to solve them.
Example A. Let x = cost of a hamburger,
y = cost of an order of fries. If two hamburgers and
an order of fries cost $7, and one hamburger and one
order of fries cost $5. What is the price of each?
2x + y = 7
x + y = 5{
A group of equations such as this is called a
system of equations.
Eq. 1
Eq. 2
We translate this information into two equations:
Systems of Linear Equations
We are to find values for x and for y that will satisfy all
equations in the system.
Systems of Linear Equations
We are to find values for x and for y that will satisfy all
equations in the system. Such a set of values is
called a solution for the system.
Systems of Linear Equations
We are to find values for x and for y that will satisfy all
equations in the system. Such a set of values is
called a solution for the system. To solve the system,
we note that the difference in the two orders is one
hamburger and the difference in price is $2.
Systems of Linear Equations
We are to find values for x and for y that will satisfy all
equations in the system. Such a set of values is
called a solution for the system. To solve the system,
we note that the difference in the two orders is one
hamburger and the difference in price is $2. So the
price of the hamburger must be $2.
Systems of Linear Equations
We are to find values for x and for y that will satisfy all
equations in the system. Such a set of values is
called a solution for the system. To solve the system,
we note that the difference in the two orders is one
hamburger and the difference in price is $2. So the
price of the hamburger must be $2. In algebra, we
subtract the equations in the system:
2x + y = 7
x + y = 5)
Eq. 1
Eq. 2
Systems of Linear Equations
We are to find values for x and for y that will satisfy all
equations in the system. Such a set of values is
called a solution for the system. To solve the system,
we note that the difference in the two orders is one
hamburger and the difference in price is $2. So the
price of the hamburger must be $2. In algebra, we
subtract the equations in the system:
2x + y = 7
x + y = 5)
x = 2
Eq. 1
Eq. 2
Systems of Linear Equations
We are to find values for x and for y that will satisfy all
equations in the system. Such a set of values is
called a solution for the system. To solve the system,
we note that the difference in the two orders is one
hamburger and the difference in price is $2. So the
price of the hamburger must be $2. In algebra, we
subtract the equations in the system:
2x + y = 7
x + y = 5)
x = 2
Eq. 1
Eq. 2
Put x = 2 back into Eq. 2, we get y = 3.
Systems of Linear Equations
We are to find values for x and for y that will satisfy all
equations in the system. Such a set of values is
called a solution for the system. To solve the system,
we note that the difference in the two orders is one
hamburger and the difference in price is $2. So the
price of the hamburger must be $2. In algebra, we
subtract the equations in the system:
2x + y = 7
x + y = 5)
x = 2
Eq. 1
Eq. 2
Put x = 2 back into Eq. 2, we get y = 3.
Hence a hamburger is $2 and an order of fries is $3.
Systems of Linear Equations
We are to find values for x and for y that will satisfy all
equations in the system. Such a set of values is
called a solution for the system. To solve the system,
we note that the difference in the two orders is one
hamburger and the difference in price is $2. So the
price of the hamburger must be $2. In algebra, we
subtract the equations in the system:
2x + y = 7
x + y = 5)
x = 2
Eq. 1
Eq. 2
Put x = 2 back into Eq. 2, we get y = 3.
Hence a hamburger is $2 and an order of fries is $3.
This is called the elimination method - we eliminate
variables by adding or subtracting two equations.
Elimination method reduces the number of
variables in the system one at a time.
Systems of Linear Equations
Elimination method reduces the number of
variables in the system one at a time. The method
changes a given system into a smaller system.
Systems of Linear Equations
Elimination method reduces the number of
variables in the system one at a time. The method
changes a given system into a smaller system. We
do this successively until the solution is clear.
Systems of Linear Equations
Elimination method reduces the number of
variables in the system one at a time. The method
changes a given system into a smaller system. We
do this successively until the solution is clear.
Systems of Linear Equations
Example B:
Let x = cost of a hamburger,
y = cost of an order of fries,
z = cost of a soda.
2 hamburgers, 3 fries and 3 soda cost $13.
1 hamburger, 2 fries and 2 soda cost $8.
3 hamburgers, 2 fries, 3 soda cost $13.
Find x, y, and z.
Elimination method reduces the number of
variables in the system one at a time. The method
changes a given system into a smaller system. We
do this successively until the solution is clear.
Systems of Linear Equations
We translate the information into a system of three
equations with three unknowns.
Example B.
Let x = cost of a hamburger,
y = cost of an order of fries,
z = cost of a soda.
2 hamburgers, 3 fries and 3 soda cost $13.
1 hamburger, 2 fries and 2 soda cost $8.
3 hamburgers, 2 fries, 3 soda cost $13.
Find x, y, and z.
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
Systems of Linear Equations
2 burgers 3 fries, 3 sodas: $13
1 burger, 2 fries and 2 sodas: $8
3 burgers, 2 fries, 3 sodas: $13
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
Select x to eliminate since there is 1x in E2.
Systems of Linear Equations
2 burgers 3 fries, 3 sodas: $13
1 burger, 2 fries and 2 sodas: $8
3 burgers, 2 fries, 3 sodas: $13
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
Select x to eliminate since there is 1x in E2.
-2*E 2 + E1:
Systems of Linear Equations
2 burgers 3 fries, 3 sodas: $13
1 burger, 2 fries and 2 sodas: $8
3 burgers, 2 fries, 3 sodas: $13
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
Select x to eliminate since there is 1x in E2.
-2*E 2 + E1:
-2x – 4y – 4z = -16
+) 2x + 3y + 3z = 13
Systems of Linear Equations
2 burgers 3 fries, 3 sodas: $13
1 burger, 2 fries and 2 sodas: $8
3 burgers, 2 fries, 3 sodas: $13
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
Select x to eliminate since there is 1x in E2.
-2*E 2 + E1:
-2x – 4y – 4z = -16
+) 2x + 3y + 3z = 13
0 – y – z = - 3
Systems of Linear Equations
2 burgers 3 fries, 3 sodas: $13
1 burger, 2 fries and 2 sodas: $8
3 burgers, 2 fries, 3 sodas: $13
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
Select x to eliminate since there is 1x in E2.
-2*E 2 + E1:
-2x – 4y – 4z = -16
+) 2x + 3y + 3z = 13
0 – y – z = - 3
-3*E 2 + E3:
Systems of Linear Equations
2 burgers 3 fries, 3 sodas: $13
1 burger, 2 fries and 2 sodas: $8
3 burgers, 2 fries, 3 sodas: $13
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
Select x to eliminate since there is 1x in E2.
-2*E 2 + E1:
-2x – 4y – 4z = -16
+) 2x + 3y + 3z = 13
0 – y – z = - 3
-3*E 2 + E3:
-3x – 6y – 6z = -24
+) 3x + 2y + 3z = 13
Systems of Linear Equations
2 burgers 3 fries, 3 sodas: $13
1 burger, 2 fries and 2 sodas: $8
3 burgers, 2 fries, 3 sodas: $13
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
Select x to eliminate since there is 1x in E2.
-2*E 2 + E1:
-2x – 4y – 4z = -16
+) 2x + 3y + 3z = 13
0 – y – z = - 3
-3*E 2 + E3:
-3x – 6y – 6z = -24
+) 3x + 2y + 3z = 13
0 – 4y – 3z = -11
Systems of Linear Equations
2 burgers 3 fries, 3 sodas: $13
1 burger, 2 fries and 2 sodas: $8
3 burgers, 2 fries, 3 sodas: $13
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
Select x to eliminate since there is 1x in E2.
-2*E 2 + E1:
-2x – 4y – 4z = -16
+) 2x + 3y + 3z = 13
0 – y – z = - 3
-3*E 2 + E3:
-3x – 6y – 6z = -24
+) 3x + 2y + 3z = 13
0 – 4y – 3z = -11
Group these into a system of two equations with
two unknowns.
Systems of Linear Equations
2 burgers 3 fries, 3 sodas: $13
1 burger, 2 fries and 2 sodas: $8
3 burgers, 2 fries, 3 sodas: $13
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
Select x to eliminate since there is 1x in E2.
-2*E 2 + E1:
-2x – 4y – 4z = -16
+) 2x + 3y + 3z = 13
0 – y – z = - 3
-3*E 2 + E3:
-3x – 6y – 6z = -24
+) 3x + 2y + 3z = 13
0 – 4y – 3z = -11
Group these into a system of two equations with
two unknowns.
Systems of Linear Equations
Hence we reduced the system to a simpler one.
2 burgers 3 fries, 3 sodas: $13
1 burger, 2 fries and 2 sodas: $8
3 burgers, 2 fries, 3 sodas: $13
– y – z = - 3
– 4y – 3z = -11{
Systems of Linear Equations
– y – z = - 3
– 4y – 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
Systems of Linear Equations
*(-1)
– y – z = - 3
– 4y – 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
Systems of Linear Equations
*(-1)
Let's eliminate z.
– y – z = - 3
– 4y – 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
Systems of Linear Equations
*(-1)
Let's eliminate z.
– y – z = - 3
– 4y – 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y – 3z = -9
Systems of Linear Equations
*(-1)
Let's eliminate z.
– y – z = - 3
– 4y – 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y – 3z = -9
y + 0 = 2
y = 2
Systems of Linear Equations
*(-1)
Let's eliminate z.
– y – z = - 3
– 4y – 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y – 3z = -9
y + 0 = 2
y = 2
To get z, set 2 for y in E4:
Systems of Linear Equations
*(-1)
Let's eliminate z.
– y – z = - 3
– 4y – 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y – 3z = -9
y + 0 = 2
y = 2
To get z, set 2 for y in E4: 2 + z = 3 οƒ  z = 1
Systems of Linear Equations
*(-1)
Let's eliminate z.
– y – z = - 3
– 4y – 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y – 3z = -9
y + 0 = 2
y = 2
To get z, set 2 for y in E4: 2 + z = 3 οƒ  z = 1
For x, set 2 for y , set 1 for z in E2:
Systems of Linear Equations
*(-1)
Let's eliminate z.
– y – z = - 3
– 4y – 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y – 3z = -9
y + 0 = 2
y = 2
To get z, set 2 for y in E4: 2 + z = 3 οƒ  z = 1
For x, set 2 for y , set 1 for z in E2:
x + 2*2 + 2*1 = 8 οƒ 
Systems of Linear Equations
*(-1)
Let's eliminate z.
– y – z = - 3
– 4y – 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y – 3z = -9
y + 0 = 2
y = 2
To get z, set 2 for y in E4: 2 + z = 3 οƒ  z = 1
For x, set 2 for y , set 1 for z in E2:
x + 2*2 + 2*1 = 8 οƒ  x + 6 = 8 οƒ  x = 2
Systems of Linear Equations
*(-1)
Let's eliminate z.
– y – z = - 3
– 4y – 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y – 3z = -9
y + 0 = 2
y = 2
To get z, set 2 for y in E4: 2 + z = 3 οƒ  z = 1
For x, set 2 for y , set 1 for z in E2:
x + 2*2 + 2*1 = 8 οƒ  x + 6 = 8 οƒ  x = 2
Systems of Linear Equations
*(-1)
Hence the hamburger costs $2, and an order of fries
costs $2 and the drink costs $1.
Let's eliminate z.
A matrix is a rectangular table of numbers.
Matrix Notation
A matrix is a rectangular table of numbers.
For example
5 2 -3
4 -1 0
-1 2 -1
6 -2 3
11 9 -4
Matrix Notation
are matrices.
A matrix is a rectangular table of numbers.
For example
5 2 -3
4 -1 0
-1 2 -1
6 -2 3
11 9 -4
Matrix Notation
are matrices.
Systems of linear equations can be put into matrices
and solved using matrix notation.
A matrix is a rectangular table of numbers.
For example
5 2 -3
4 -1 0
-1 2 -1
6 -2 3
11 9 -4
Matrix Notation
are matrices.
Systems of linear equations can be put into matrices
and solved using matrix notation.
x + 4y = -7
2x – 3y = 8{
For example, the system
1 4 -7
2 -3 8
may be written as the matrix:
x y #
A matrix is a rectangular table of numbers.
For example
5 2 -3
4 -1 0
-1 2 -1
6 -2 3
11 9 -4
Matrix Notation
are matrices.
Systems of linear equations can be put into matrices
and solved using matrix notation.
x + 4y = -7
2x – 3y = 8{
For example, the system
1 4 -7
2 -3 8
may be written as the matrix:
x y #
This is called the augmented matrix for the system.
A matrix is a rectangular table of numbers.
For example
5 2 -3
4 -1 0
-1 2 -1
6 -2 3
11 9 -4
Matrix Notation
are matrices.
Systems of linear equations can be put into matrices
and solved using matrix notation.
x + 4y = -7
2x – 3y = 8{
For example, the system
1 4 -7
2 -3 8
may be written as the matrix:
x y #
This is called the augmented matrix for the system.
Each row of the matrix corresponds to an equation,
each column corresponds to a variable and the last
column corresponds to numbers.
Matrix Notation
An augmented matrix can be easily converted back to
a system .
Matrix Notation
An augmented matrix can be easily converted back to
a system .
For example, the augmented matrix
2 -3 8
1 4 -7
is the system x + 4y = -7{2x – 3y = 8
Operations of the equations correspond to operations
of rows in the matrices.
Matrix Notation
An augmented matrix can be easily converted back to
a system .
2 -3 8
1 4 -7
is the system x + 4y = -7{2x – 3y = 8
For example, the augmented matrix
Operations of the equations correspond to operations
of rows in the matrices. Three such operations are
important. These are the elementary row operations:
Matrix Notation
An augmented matrix can be easily converted back to
a system .
2 -3 8
1 4 -7
is the system x + 4y = -7{2x – 3y = 8
For example, the augmented matrix
Matrix Notation
I. Switch two rows.
An augmented matrix can be easily converted back to
a system .
2 -3 8
1 4 -7
is the system x + 4y = -7{2x – 3y = 8
Operations of the equations correspond to operations
of rows in the matrices. Three such operations are
important. These are the elementary row operations:
For example, the augmented matrix
Matrix Notation
I. Switch two rows. Switching row i with row j is
notated as Ri Rj.
An augmented matrix can be easily converted back to
a system .
2 -3 8
1 4 -7
is the system x + 4y = -7{2x – 3y = 8
Operations of the equations correspond to operations
of rows in the matrices. Three such operations are
important. These are the elementary row operations:
For example, the augmented matrix
Matrix Notation
1 4 -7
2 -3 8
For example,
R1 R2
I. Switch two rows. Switching row i with row j is
notated as Ri Rj.
An augmented matrix can be easily converted back to
a system .
2 -3 8
1 4 -7
is the system x + 4y = -7{2x – 3y = 8
Operations of the equations correspond to operations
of rows in the matrices. Three such operations are
important. These are the elementary row operations:
For example, the augmented matrix
Matrix Notation
1 4 -7
2 -3 8
For example,
R1 R2 2 -3 8
1 4 -7
I. Switch two rows. Switching row i with row j is
notated as Ri Rj.
An augmented matrix can be easily converted back to
a system .
2 -3 8
1 4 -7
is the system x + 4y = -7{2x – 3y = 8
Operations of the equations correspond to operations
of rows in the matrices. Three such operations are
important. These are the elementary row operations:
For example, the augmented matrix
Matrix Notation
II. Multiply a row by a constant k = 0.
Matrix Notation
II. Multiply a row by a constant k = 0. Multiply row i by
k is notated as k*Ri.
Matrix Notation
II. Multiply a row by a constant k = 0. Multiply row i by
k is notated as k*Ri.
1 4 -7
2 -3 8
-3*R2
For example,
Matrix Notation
II. Multiply a row by a constant k = 0. Multiply row i by
k is notated as k*Ri.
1 4 -7
2 -3 8
-3*R2 1 4 -7
-6 9 -24
For example,
III. Add the multiple of a row to another row.
Matrix Notation
II. Multiply a row by a constant k = 0. Multiply row i by
k is notated as k*Ri.
1 4 -7
2 -3 8
-3*R2 1 4 -7
-6 9 -24
For example,
III. Add the multiple of a row to another row. k times
row i added to row j is notated as β€œk*Ri add οƒ  Rj”.
Matrix Notation
II. Multiply a row by a constant k = 0. Multiply row i by
k is notated as k*Ri.
1 4 -7
2 -3 8
-3*R2 1 4 -7
-6 9 -24
For example,
III. Add the multiple of a row to another row. k times
row i added to row j is notated as β€œk*Ri add οƒ  Rj”.
1 4 -7
2 -3 8
For example,
-2*R1 add οƒ  R2
Matrix Notation
II. Multiply a row by a constant k = 0. Multiply row i by
k is notated as k*Ri.
1 4 -7
2 -3 8
-3*R2 1 4 -7
-6 9 -24
For example,
III. Add the multiple of a row to another row. k times
row i added to row j is notated as β€œk*Ri add οƒ  Rj”.
1 4 -7
2 -3 8
For example,
-2*R1 add οƒ  R2
-2 -8 14
write a copy of -2*R1
Matrix Notation
II. Multiply a row by a constant k = 0. Multiply row i by
k is notated as k*Ri.
1 4 -7
2 -3 8
-3*R2 1 4 -7
-6 9 -24
For example,
III. Add the multiple of a row to another row. k times
row i added to row j is notated as β€œk*Ri add οƒ  Rj”.
1 4 -7
2 -3 8
For example,
-2*R1 add οƒ  R2 1 4 -7
0 -11 22
-2 -8 14
write a copy of -2*R1
Matrix Notation
II. Multiply a row by a constant k = 0. Multiply row i by
k is notated as k*Ri.
1 4 -7
2 -3 8
-3*R2 1 4 -7
-6 9 -24
For example,
III. Add the multiple of a row to another row. k times
row i added to row j is notated as β€œk*Ri add οƒ  Rj”.
1 4 -7
2 -3 8
For example,
-2*R1 add οƒ  R2 1 4 -7
0 -11 22
-2 -8 14
write a copy of -2*R1
Fact: Performing elementary row operations on a
matrix does not change the solution of the system.
Matrix Notation
II. Multiply a row by a constant k = 0. Multiply row i by
k is notated as k*Ri.
1 4 -7
2 -3 8
-3*R2 1 4 -7
-6 9 -24
For example,
Matrix Notation
The elimination method may be carried out with
matrix notation.
Elimination Method in Matrix Notation:
Matrix Notation
The elimination method may be carried out with
matrix notation.
Matrix Notation
The elimination method may be carried out with
matrix notation.
Elimination Method in Matrix Notation:
1. Apply row operations to transform the matrix
* * * *
* * * *
* * * *
Row operations
Matrix Notation
The elimination method may be carried out with
matrix notation.
Elimination Method in Matrix Notation:
1. Apply row operations to transform the matrix
* * * *
* * * *
* * * *
Row operations
Matrix Notation
The elimination method may be carried out with
matrix notation.
Elimination Method in Matrix Notation:
1. Apply row operations to transform the matrix to the
upper diagonal form where all the entries below the
main diagonal (the lower left triangular region) are 0 .
* * * *
* * * *
* * * *
Row operations * * * *
* * *
* *
0
0 0
Matrix Notation
The elimination method may be carried out with
matrix notation.
Elimination Method in Matrix Notation:
1. Apply row operations to transform the matrix to the
upper diagonal form where all the entries below the
main diagonal (the lower left triangular region) are 0 .
* * * *
* * * *
* * * *
Row operations * * * *
* * *
* *
0
0 0
2. Starting from the bottom row, get the answer
for one of the variables.
Matrix Notation
The elimination method may be carried out with
matrix notation.
Elimination Method in Matrix Notation:
1. Apply row operations to transform the matrix to the
upper diagonal form where all the entries below the
main diagonal (the lower left triangular region) are 0 .
* * * *
* * * *
* * * *
Row operations * * * *
* * *
* *
0
0 0
2. Starting from the bottom row, get the answer
for one of the variables. Then go up one row, use
the solution already obtained to get another answer of
another variable.
Matrix Notation
The elimination method may be carried out with
matrix notation.
Elimination Method in Matrix Notation:
1. Apply row operations to transform the matrix to the
upper diagonal form where all the entries below the
main diagonal (the lower left triangular region) are 0 .
Elimination Method in Matrix Notation:
1. Apply row operations to transform the matrix to the
upper diagonal form where all the entries below the
main diagonal (the lower left triangular region) are 0 .
* * * *
* * * *
* * * *
Row operations * * * *
* * *
* *
0
0 0
2. Starting from the bottom row, get the answer
for one of the variables. Then go up one row, use
the solution already obtained to get another answer of
another variable. Repeat the process, working from
the bottom row to the top row to extract all solutions.
Matrix Notation
The elimination method may be carried out with
matrix notation.
x + 4y = -7
2x – 3y = 8{ Eq. 1
Eq. 2
Example C: Solve using matrix notation:
Matrix Notation
1 4 -7
2 -3 8
x + 4y = -7
2x – 3y = 8{ Eq. 1
Eq. 2
Example C: Solve using matrix notation:
Put the system into a matrix:
Matrix Notation
1 4 -7
2 -3 8
-2*R1 add οƒ  R2
x + 4y = -7
2x – 3y = 8{ Eq. 1
Eq. 2
Example C: Solve using matrix notation:
Put the system into a matrix:
Matrix Notation
1 4 -7
2 -3 8
-2*R1 add οƒ  R2
-2 -8 14
x + 4y = -7
2x – 3y = 8{ Eq. 1
Eq. 2
Example C: Solve using matrix notation:
Put the system into a matrix:
Matrix Notation
1 4 -7
2 -3 8
-2*R1 add οƒ  R2 1 4 -7
0 -11 22
-2 -8 14
x + 4y = -7
2x – 3y = 8{ Eq. 1
Eq. 2
Example C: Solve using matrix notation:
Put the system into a matrix:
Matrix Notation
1 4 -7
2 -3 8
-2*R1 add οƒ  R2 1 4 -7
0 -11 22
-2 -8 14
x + 4y = -7
2x – 3y = 8{ Eq. 1
Eq. 2
Example C: Solve using matrix notation:
Put the system into a matrix:
Starting from the bottom row: -11y = 22 οƒ  y = -2
Matrix Notation
1 4 -7
2 -3 8
-2*R1 add οƒ  R2 1 4 -7
0 -11 22
-2 -8 14
x + 4y = -7
2x – 3y = 8{ Eq. 1
Eq. 2
Example C: Solve using matrix notation:
Put the system into a matrix:
Starting from the bottom row: -11y = 22 οƒ  y = -2
Go up one row to R1 and set y = -2:
Matrix Notation
1 4 -7
2 -3 8
-2*R1 add οƒ  R2 1 4 -7
0 -11 22
-2 -8 14
x + 4y = -7
2x – 3y = 8{ Eq. 1
Eq. 2
Example C: Solve using matrix notation:
Put the system into a matrix:
Starting from the bottom row: -11y = 22 οƒ  y = -2
Go up one row to R1 and set y = -2:
x + 4y = -7
x + 4(-2) = -7
Matrix Notation
1 4 -7
2 -3 8
-2*R1 add οƒ  R2 1 4 -7
0 -11 22
-2 -8 14
x + 4y = -7
2x – 3y = 8{ Eq. 1
Eq. 2
Example C: Solve using matrix notation:
Put the system into a matrix:
Starting from the bottom row: -11y = 22 οƒ  y = -2
Go up one row to R1 and set y = -2:
x + 4y = -7
x + 4(-2) = -7 οƒ  x = 1
Matrix Notation
Hence the solution is {x = 1, y = -2}
or as the ordered pair (1, -2).
Example D: Solve using matrix notation:
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
Matrix Notation
Example D: Solve using matrix notation:
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
2 3 3 13
Put the system into a matrix:
1 2 2 8
3 2 3 13
Matrix Notation
Example D: Solve using matrix notation:
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
2 3 3 13 R1 R2
Put the system into a matrix:
1 2 2 8
3 2 3 13
2 3 3 13
1 2 2 8
3 2 3 13
Matrix Notation
Example D: Solve using matrix notation:
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
2 3 3 13 R1 R2
-2 -4 -4 -16Put the system into a matrix:
1 2 2 8
3 2 3 13
2 3 3 13
1 2 2 8
3 2 3 13
-2*R1 add R2
Matrix Notation
Example D: Solve using matrix notation:
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
2 3 3 13 R1 R2
-2 -4 -4 -16Put the system into a matrix:
1 2 2 8
3 2 3 13
2 3 3 13
1 2 2 8
3 2 3 13
-2*R1 add R2
0 -1 -1 -3
1 2 2 8
3 2 3 13
Matrix Notation
Example D: Solve using matrix notation:
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
2 3 3 13 R1 R2
-2 -4 -4 -16Put the system into a matrix:
1 2 2 8
3 2 3 13
2 3 3 13
1 2 2 8
3 2 3 13
-2*R1 add R2
0 -1 -1 -3
1 2 2 8
3 2 3 13
-3* R1 add R3
-3 -6 -6 -24
Matrix Notation
Example D: Solve using matrix notation:
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
2 3 3 13 R1 R2
-2 -4 -4 -16Put the system into a matrix:
1 2 2 8
3 2 3 13
2 3 3 13
1 2 2 8
3 2 3 13
-2*R1 add R2
0 -1 -1 -3
1 2 2 8
3 2 3 13
-3* R1 add R3
-3 -6 -6 -24
0 -1 -1 -3
1 2 2 8
0 -4 -3 -11
Matrix Notation
Example D: Solve using matrix notation:
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
2 3 3 13 R1 R2
-2 -4 -4 -16Put the system into a matrix:
1 2 2 8
3 2 3 13
2 3 3 13
1 2 2 8
3 2 3 13
-2*R1 add R2
0 -1 -1 -3
1 2 2 8
3 2 3 13
-3* R1 add R3
-3 -6 -6 -24
0 -1 -1 -3
1 2 2 8
0 -4 -3 -11
-4*R2 add R3
0 4 4 12
Matrix Notation
Example D: Solve using matrix notation:
2x + 3y + 3z = 13
x + 2y + 2z = 8
3x + 2y + 3z = 13
{
E 1
E 2
E 3
2 3 3 13 R1 R2
-2 -4 -4 -16Put the system into a matrix:
1 2 2 8
3 2 3 13
2 3 3 13
1 2 2 8
3 2 3 13
-2*R1 add R2
0 -1 -1 -3
1 2 2 8
3 2 3 13
-3* R1 add R3
-3 -6 -6 -24
0 -1 -1 -3
1 2 2 8
0 -4 -3 -11
-4*R2 add R3
0 4 4 12
0 -1 -1 -3
1 2 2 8
0 0 1 1
Matrix Notation
0 -1 -1 -3
1 2 2 8
0 0 1 1
Matrix Notation
Extract the solution starting
from the bottom row.
0 -1 -1 -3
1 2 2 8
0 0 1 1
From R3, we get z = 1.
Matrix Notation
Extract the solution starting
from the bottom row.
0 -1 -1 -3
1 2 2 8
0 0 1 1
From R3, we get z = 1.
Go up one row to R2, we get
-y – z = -3
-y – (1) = -3
Matrix Notation
Extract the solution starting
from the bottom row.
0 -1 -1 -3
1 2 2 8
0 0 1 1
From R3, we get z = 1.
Go up one row to R2, we get
-y – z = -3
-y – (1) = -3
3 – 1 = y
2 = y
Matrix Notation
Extract the solution starting
from the bottom row.
0 -1 -1 -3
1 2 2 8
0 0 1 1
From R3, we get z = 1.
Go up one row to R2, we get
-y – z = -3
-y – (1) = -3
3 – 1 = y
2 = y
Up to R1, we get x + 2y + 2z = 8
x + 2(2) + 2(1) = 8
Matrix Notation
Extract the solution starting
from the bottom row.
0 -1 -1 -3
1 2 2 8
0 0 1 1
From R3, we get z = 1.
Go up one row to R2, we get
-y – z = -3
-y – (1) = -3
3 – 1 = y
2 = y
Up to R1, we get x + 2y + 2z = 8
x + 2(2) + 2(1) = 8
x + 6 = 8
x = 2
Matrix Notation
Extract the solution starting
from the bottom row.
0 -1 -1 -3
1 2 2 8
0 0 1 1
From R3, we get z = 1.
Go up one row to R2, we get
-y – z = -3
-y – (1) = -3
3 – 1 = y
2 = y
Up to R1, we get x + 2y + 2z = 8
x + 2(2) + 2(1) = 8
x + 6 = 8
x = 2
So the solution is (2, 2, 1).
Matrix Notation
Extract the solution starting
from the bottom row.
A soda costs $1, a hot dog costs $3 and an ice cream costs
$2. Find the cost of the following orders.
1) 2 sodas, 2 hotdogs and 1 ice cream. ______
2) 3 sodas, 3 hotdogs and 2 ice creams. ______
3) 4 sodas, 6 hotdogs and no ice creams. ______
4) 8 sodas, 6 hotdogs and 7 ice creams. ______
Now let a soda cost $x, a hot dog cost $y and an ice cream
cost $z. Find an algebraic expression for the cost of the
above orders.
5) _______________ 6) _____________
7) _____________ 8) _____________
9) If order #1 is $15, order #2 is $24 and order #3 is $32,
write the system of equations and solve.
10) If order #1 is $17, order #3 is $36 and order #4 is $67,
write the system of equations and solve.
Systems of Linear Equations
1) $10 3) $22 5) 2x +2y + z 7) 4x + 6y
9) 2x + 2y + z = $15
3x + 3y + 2z = $24
4x + 6y = $32.
x = 2, y = 4, z = 3
Systems of Linear Equations
11) x + 2y = 7
4y = 8
x = 3, y = 2
13) x + 2y + 4z = 3
y + z = 4
z = 6
x = -17, y = -2, z =6
13) 2 1 1
0 -2.5 7.5
17) -1 2 2 1
1 1 1 2
2 2 1 1
(Answers to the odd problems)

More Related Content

What's hot

13 graphs of factorable polynomials x
13 graphs of factorable polynomials x13 graphs of factorable polynomials x
13 graphs of factorable polynomials xmath260
Β 
16 slopes and difference quotient x
16 slopes and difference quotient x16 slopes and difference quotient x
16 slopes and difference quotient xmath260
Β 
27 calculation with log and exp x
27 calculation with log and exp x27 calculation with log and exp x
27 calculation with log and exp xmath260
Β 
11 graphs of first degree functions x
11 graphs of first degree functions x11 graphs of first degree functions x
11 graphs of first degree functions xmath260
Β 
12 graphs of second degree functions x
12 graphs of second degree functions x12 graphs of second degree functions x
12 graphs of second degree functions xmath260
Β 
15 translations of graphs x
15 translations of graphs x15 translations of graphs x
15 translations of graphs xmath260
Β 
26 the logarithm functions x
26 the logarithm functions x26 the logarithm functions x
26 the logarithm functions xmath260
Β 
1.0 factoring trinomials the ac method and making lists-x
1.0 factoring trinomials  the ac method and making lists-x1.0 factoring trinomials  the ac method and making lists-x
1.0 factoring trinomials the ac method and making lists-xmath260
Β 
18Ellipses-x.pptx
18Ellipses-x.pptx18Ellipses-x.pptx
18Ellipses-x.pptxmath260
Β 
7 sign charts of factorable formulas y
7 sign charts of factorable formulas y7 sign charts of factorable formulas y
7 sign charts of factorable formulas ymath260
Β 
10 rectangular coordinate system x
10 rectangular coordinate system x10 rectangular coordinate system x
10 rectangular coordinate system xmath260
Β 
14 graphs of factorable rational functions x
14 graphs of factorable rational functions x14 graphs of factorable rational functions x
14 graphs of factorable rational functions xmath260
Β 
23 looking for real roots of real polynomials x
23 looking for real roots of real polynomials x23 looking for real roots of real polynomials x
23 looking for real roots of real polynomials xmath260
Β 
28 more on log and exponential equations x
28 more on log and exponential equations x28 more on log and exponential equations x
28 more on log and exponential equations xmath260
Β 
18 ellipses x
18 ellipses x18 ellipses x
18 ellipses xmath260
Β 
1.3 solving equations y
1.3 solving equations y1.3 solving equations y
1.3 solving equations ymath260
Β 
3 algebraic expressions y
3 algebraic expressions y3 algebraic expressions y
3 algebraic expressions ymath266
Β 
17 conic sections circles-x
17 conic sections circles-x17 conic sections circles-x
17 conic sections circles-xmath260
Β 
8 inequalities and sign charts x
8 inequalities and sign charts x8 inequalities and sign charts x
8 inequalities and sign charts xmath260
Β 
5 complex numbers y
5 complex numbers y5 complex numbers y
5 complex numbers ymath260
Β 

What's hot (20)

13 graphs of factorable polynomials x
13 graphs of factorable polynomials x13 graphs of factorable polynomials x
13 graphs of factorable polynomials x
Β 
16 slopes and difference quotient x
16 slopes and difference quotient x16 slopes and difference quotient x
16 slopes and difference quotient x
Β 
27 calculation with log and exp x
27 calculation with log and exp x27 calculation with log and exp x
27 calculation with log and exp x
Β 
11 graphs of first degree functions x
11 graphs of first degree functions x11 graphs of first degree functions x
11 graphs of first degree functions x
Β 
12 graphs of second degree functions x
12 graphs of second degree functions x12 graphs of second degree functions x
12 graphs of second degree functions x
Β 
15 translations of graphs x
15 translations of graphs x15 translations of graphs x
15 translations of graphs x
Β 
26 the logarithm functions x
26 the logarithm functions x26 the logarithm functions x
26 the logarithm functions x
Β 
1.0 factoring trinomials the ac method and making lists-x
1.0 factoring trinomials  the ac method and making lists-x1.0 factoring trinomials  the ac method and making lists-x
1.0 factoring trinomials the ac method and making lists-x
Β 
18Ellipses-x.pptx
18Ellipses-x.pptx18Ellipses-x.pptx
18Ellipses-x.pptx
Β 
7 sign charts of factorable formulas y
7 sign charts of factorable formulas y7 sign charts of factorable formulas y
7 sign charts of factorable formulas y
Β 
10 rectangular coordinate system x
10 rectangular coordinate system x10 rectangular coordinate system x
10 rectangular coordinate system x
Β 
14 graphs of factorable rational functions x
14 graphs of factorable rational functions x14 graphs of factorable rational functions x
14 graphs of factorable rational functions x
Β 
23 looking for real roots of real polynomials x
23 looking for real roots of real polynomials x23 looking for real roots of real polynomials x
23 looking for real roots of real polynomials x
Β 
28 more on log and exponential equations x
28 more on log and exponential equations x28 more on log and exponential equations x
28 more on log and exponential equations x
Β 
18 ellipses x
18 ellipses x18 ellipses x
18 ellipses x
Β 
1.3 solving equations y
1.3 solving equations y1.3 solving equations y
1.3 solving equations y
Β 
3 algebraic expressions y
3 algebraic expressions y3 algebraic expressions y
3 algebraic expressions y
Β 
17 conic sections circles-x
17 conic sections circles-x17 conic sections circles-x
17 conic sections circles-x
Β 
8 inequalities and sign charts x
8 inequalities and sign charts x8 inequalities and sign charts x
8 inequalities and sign charts x
Β 
5 complex numbers y
5 complex numbers y5 complex numbers y
5 complex numbers y
Β 

Viewers also liked

Matrix and its operation (addition, subtraction, multiplication)
Matrix and its operation (addition, subtraction, multiplication)Matrix and its operation (addition, subtraction, multiplication)
Matrix and its operation (addition, subtraction, multiplication)NirnayMukharjee
Β 
system linear equations and matrices
 system linear equations and matrices system linear equations and matrices
system linear equations and matricesAditya Vaishampayan
Β 
2002 it in educational management organic school info-systems-decision making...
2002 it in educational management organic school info-systems-decision making...2002 it in educational management organic school info-systems-decision making...
2002 it in educational management organic school info-systems-decision making...Christopher Thorn
Β 
Matrices - Mathematics
Matrices - MathematicsMatrices - Mathematics
Matrices - MathematicsDrishti Bhalla
Β 
Linear Functions And Matrices
Linear Functions And MatricesLinear Functions And Matrices
Linear Functions And Matricesandrewhickson
Β 
Making your School Decision
Making your School DecisionMaking your School Decision
Making your School DecisionSomik Raha
Β 
Educational administration and management
Educational administration and managementEducational administration and management
Educational administration and managementteachertraining
Β 
Beginning direct3d gameprogrammingmath05_matrices_20160515_jintaeks
Beginning direct3d gameprogrammingmath05_matrices_20160515_jintaeksBeginning direct3d gameprogrammingmath05_matrices_20160515_jintaeks
Beginning direct3d gameprogrammingmath05_matrices_20160515_jintaeksJinTaek Seo
Β 
Decision Making : Management Function
Decision Making : Management FunctionDecision Making : Management Function
Decision Making : Management FunctionSanchit
Β 
Matlab for Electrical Engineers
Matlab for Electrical EngineersMatlab for Electrical Engineers
Matlab for Electrical EngineersManish Joshi
Β 
Algebraic Mathematics of Linear Inequality & System of Linear Inequality
Algebraic Mathematics of Linear Inequality & System of Linear InequalityAlgebraic Mathematics of Linear Inequality & System of Linear Inequality
Algebraic Mathematics of Linear Inequality & System of Linear InequalityJacqueline Chau
Β 
Advanced MATLAB Tutorial for Engineers & Scientists
Advanced MATLAB Tutorial for Engineers & ScientistsAdvanced MATLAB Tutorial for Engineers & Scientists
Advanced MATLAB Tutorial for Engineers & ScientistsRay Phan
Β 
Ch 01 MATLAB Applications in Chemical Engineering_ι™³ε₯‡δΈ­ζ•™ζŽˆζ•™ε­ΈζŠ•ε½±η‰‡
Ch 01 MATLAB Applications in Chemical Engineering_ι™³ε₯‡δΈ­ζ•™ζŽˆζ•™ε­ΈζŠ•ε½±η‰‡Ch 01 MATLAB Applications in Chemical Engineering_ι™³ε₯‡δΈ­ζ•™ζŽˆζ•™ε­ΈζŠ•ε½±η‰‡
Ch 01 MATLAB Applications in Chemical Engineering_ι™³ε₯‡δΈ­ζ•™ζŽˆζ•™ε­ΈζŠ•ε½±η‰‡Chyi-Tsong Chen
Β 
MATRICES
MATRICESMATRICES
MATRICESfaijmsk
Β 
Linear Algebra and Matrix
Linear Algebra and MatrixLinear Algebra and Matrix
Linear Algebra and Matrixitutor
Β 
presentation on matrix
 presentation on matrix presentation on matrix
presentation on matrixNikhi Jain
Β 
Matrices And Application Of Matrices
Matrices And Application Of MatricesMatrices And Application Of Matrices
Matrices And Application Of Matricesmailrenuka
Β 

Viewers also liked (20)

Matrix and its operation (addition, subtraction, multiplication)
Matrix and its operation (addition, subtraction, multiplication)Matrix and its operation (addition, subtraction, multiplication)
Matrix and its operation (addition, subtraction, multiplication)
Β 
system linear equations and matrices
 system linear equations and matrices system linear equations and matrices
system linear equations and matrices
Β 
2002 it in educational management organic school info-systems-decision making...
2002 it in educational management organic school info-systems-decision making...2002 it in educational management organic school info-systems-decision making...
2002 it in educational management organic school info-systems-decision making...
Β 
Matrices - Mathematics
Matrices - MathematicsMatrices - Mathematics
Matrices - Mathematics
Β 
Linear Functions And Matrices
Linear Functions And MatricesLinear Functions And Matrices
Linear Functions And Matrices
Β 
M a t r i k s
M a t r i k sM a t r i k s
M a t r i k s
Β 
Making your School Decision
Making your School DecisionMaking your School Decision
Making your School Decision
Β 
Educational administration and management
Educational administration and managementEducational administration and management
Educational administration and management
Β 
Beginning direct3d gameprogrammingmath05_matrices_20160515_jintaeks
Beginning direct3d gameprogrammingmath05_matrices_20160515_jintaeksBeginning direct3d gameprogrammingmath05_matrices_20160515_jintaeks
Beginning direct3d gameprogrammingmath05_matrices_20160515_jintaeks
Β 
Decision Making : Management Function
Decision Making : Management FunctionDecision Making : Management Function
Decision Making : Management Function
Β 
Decision Making - Management Principles
Decision Making - Management PrinciplesDecision Making - Management Principles
Decision Making - Management Principles
Β 
Matlab for Electrical Engineers
Matlab for Electrical EngineersMatlab for Electrical Engineers
Matlab for Electrical Engineers
Β 
Algebraic Mathematics of Linear Inequality & System of Linear Inequality
Algebraic Mathematics of Linear Inequality & System of Linear InequalityAlgebraic Mathematics of Linear Inequality & System of Linear Inequality
Algebraic Mathematics of Linear Inequality & System of Linear Inequality
Β 
Advanced MATLAB Tutorial for Engineers & Scientists
Advanced MATLAB Tutorial for Engineers & ScientistsAdvanced MATLAB Tutorial for Engineers & Scientists
Advanced MATLAB Tutorial for Engineers & Scientists
Β 
Ch 01 MATLAB Applications in Chemical Engineering_ι™³ε₯‡δΈ­ζ•™ζŽˆζ•™ε­ΈζŠ•ε½±η‰‡
Ch 01 MATLAB Applications in Chemical Engineering_ι™³ε₯‡δΈ­ζ•™ζŽˆζ•™ε­ΈζŠ•ε½±η‰‡Ch 01 MATLAB Applications in Chemical Engineering_ι™³ε₯‡δΈ­ζ•™ζŽˆζ•™ε­ΈζŠ•ε½±η‰‡
Ch 01 MATLAB Applications in Chemical Engineering_ι™³ε₯‡δΈ­ζ•™ζŽˆζ•™ε­ΈζŠ•ε½±η‰‡
Β 
MATRICES
MATRICESMATRICES
MATRICES
Β 
Linear Algebra and Matrix
Linear Algebra and MatrixLinear Algebra and Matrix
Linear Algebra and Matrix
Β 
presentation on matrix
 presentation on matrix presentation on matrix
presentation on matrix
Β 
Matrices And Application Of Matrices
Matrices And Application Of MatricesMatrices And Application Of Matrices
Matrices And Application Of Matrices
Β 
Educational management planning
Educational management planningEducational management planning
Educational management planning
Β 

Similar to Solve Systems of Linear Equations Using Elimination Method (40

56 system of linear equations
56 system of linear equations56 system of linear equations
56 system of linear equationsalg1testreview
Β 
6 system of linear equations i x
6 system of linear equations i x6 system of linear equations i x
6 system of linear equations i xTzenma
Β 
3 3 systems of linear equations 1
3 3 systems of linear equations 13 3 systems of linear equations 1
3 3 systems of linear equations 1math123a
Β 
4.3 system of linear equations 1
4.3 system of linear equations 14.3 system of linear equations 1
4.3 system of linear equations 1math123c
Β 
81 systems of linear equations 1
81 systems of linear equations 181 systems of linear equations 1
81 systems of linear equations 1math126
Β 
4.4 system of linear equations 2
4.4 system of linear equations 24.4 system of linear equations 2
4.4 system of linear equations 2math123c
Β 
82 systems of linear equations 2
82 systems of linear equations 282 systems of linear equations 2
82 systems of linear equations 2math126
Β 
35 Special Cases System of Linear Equations-x.pptx
35 Special Cases System of Linear Equations-x.pptx35 Special Cases System of Linear Equations-x.pptx
35 Special Cases System of Linear Equations-x.pptxmath260
Β 
Ppt materi spltv pembelajaran 1 kelas x
Ppt materi spltv pembelajaran 1 kelas xPpt materi spltv pembelajaran 1 kelas x
Ppt materi spltv pembelajaran 1 kelas xMartiwiFarisa
Β 
2linear equations i x
2linear equations i x2linear equations i x
2linear equations i xTzenma
Β 
2 2linear equations i
2 2linear equations i2 2linear equations i
2 2linear equations imath123a
Β 
3 linear equations
3 linear equations3 linear equations
3 linear equationselem-alg-sample
Β 
42 linear equations
42 linear equations42 linear equations
42 linear equationsalg1testreview
Β 
Solving linear systems by the substitution method
Solving linear systems by the substitution methodSolving linear systems by the substitution method
Solving linear systems by the substitution methodbutterflyrose0411
Β 
Systems of equations by graphing by graphing sect 6 1
Systems of equations by graphing by graphing sect 6 1Systems of equations by graphing by graphing sect 6 1
Systems of equations by graphing by graphing sect 6 1tty16922
Β 
A1, 6 1, solving systems by graphing (rev)
A1, 6 1, solving systems by graphing (rev)A1, 6 1, solving systems by graphing (rev)
A1, 6 1, solving systems by graphing (rev)kstraka
Β 
LINEAR EQUATION IN TWO VARIABLES
LINEAR EQUATION IN TWO VARIABLESLINEAR EQUATION IN TWO VARIABLES
LINEAR EQUATION IN TWO VARIABLESManah Chhabra
Β 
3 4 systems of linear equations 2
3 4 systems of linear equations 23 4 systems of linear equations 2
3 4 systems of linear equations 2math123a
Β 
6.1 system of linear equations and matrices t
6.1 system of linear equations and matrices t6.1 system of linear equations and matrices t
6.1 system of linear equations and matrices tmath260
Β 

Similar to Solve Systems of Linear Equations Using Elimination Method (40 (20)

56 system of linear equations
56 system of linear equations56 system of linear equations
56 system of linear equations
Β 
6 system of linear equations i x
6 system of linear equations i x6 system of linear equations i x
6 system of linear equations i x
Β 
3 3 systems of linear equations 1
3 3 systems of linear equations 13 3 systems of linear equations 1
3 3 systems of linear equations 1
Β 
4.3 system of linear equations 1
4.3 system of linear equations 14.3 system of linear equations 1
4.3 system of linear equations 1
Β 
81 systems of linear equations 1
81 systems of linear equations 181 systems of linear equations 1
81 systems of linear equations 1
Β 
4.4 system of linear equations 2
4.4 system of linear equations 24.4 system of linear equations 2
4.4 system of linear equations 2
Β 
82 systems of linear equations 2
82 systems of linear equations 282 systems of linear equations 2
82 systems of linear equations 2
Β 
35 Special Cases System of Linear Equations-x.pptx
35 Special Cases System of Linear Equations-x.pptx35 Special Cases System of Linear Equations-x.pptx
35 Special Cases System of Linear Equations-x.pptx
Β 
Ppt materi spltv pembelajaran 1 kelas x
Ppt materi spltv pembelajaran 1 kelas xPpt materi spltv pembelajaran 1 kelas x
Ppt materi spltv pembelajaran 1 kelas x
Β 
2linear equations i x
2linear equations i x2linear equations i x
2linear equations i x
Β 
2 2linear equations i
2 2linear equations i2 2linear equations i
2 2linear equations i
Β 
3 linear equations
3 linear equations3 linear equations
3 linear equations
Β 
42 linear equations
42 linear equations42 linear equations
42 linear equations
Β 
42 linear equations
42 linear equations42 linear equations
42 linear equations
Β 
Solving linear systems by the substitution method
Solving linear systems by the substitution methodSolving linear systems by the substitution method
Solving linear systems by the substitution method
Β 
Systems of equations by graphing by graphing sect 6 1
Systems of equations by graphing by graphing sect 6 1Systems of equations by graphing by graphing sect 6 1
Systems of equations by graphing by graphing sect 6 1
Β 
A1, 6 1, solving systems by graphing (rev)
A1, 6 1, solving systems by graphing (rev)A1, 6 1, solving systems by graphing (rev)
A1, 6 1, solving systems by graphing (rev)
Β 
LINEAR EQUATION IN TWO VARIABLES
LINEAR EQUATION IN TWO VARIABLESLINEAR EQUATION IN TWO VARIABLES
LINEAR EQUATION IN TWO VARIABLES
Β 
3 4 systems of linear equations 2
3 4 systems of linear equations 23 4 systems of linear equations 2
3 4 systems of linear equations 2
Β 
6.1 system of linear equations and matrices t
6.1 system of linear equations and matrices t6.1 system of linear equations and matrices t
6.1 system of linear equations and matrices t
Β 

More from math260

36 Matrix Algebra-x.pptx
36 Matrix Algebra-x.pptx36 Matrix Algebra-x.pptx
36 Matrix Algebra-x.pptxmath260
Β 
1 exponents yz
1 exponents yz1 exponents yz
1 exponents yzmath260
Β 
9 the basic language of functions x
9 the basic language of functions x9 the basic language of functions x
9 the basic language of functions xmath260
Β 
19 more parabolas a& hyperbolas (optional) x
19 more parabolas a& hyperbolas (optional) x19 more parabolas a& hyperbolas (optional) x
19 more parabolas a& hyperbolas (optional) xmath260
Β 
11 graphs of first degree functions x
11 graphs of first degree functions x11 graphs of first degree functions x
11 graphs of first degree functions xmath260
Β 
9 the basic language of functions x
9 the basic language of functions x9 the basic language of functions x
9 the basic language of functions xmath260
Β 
22 the fundamental theorem of algebra x
22 the fundamental theorem of algebra x22 the fundamental theorem of algebra x
22 the fundamental theorem of algebra xmath260
Β 

More from math260 (7)

36 Matrix Algebra-x.pptx
36 Matrix Algebra-x.pptx36 Matrix Algebra-x.pptx
36 Matrix Algebra-x.pptx
Β 
1 exponents yz
1 exponents yz1 exponents yz
1 exponents yz
Β 
9 the basic language of functions x
9 the basic language of functions x9 the basic language of functions x
9 the basic language of functions x
Β 
19 more parabolas a& hyperbolas (optional) x
19 more parabolas a& hyperbolas (optional) x19 more parabolas a& hyperbolas (optional) x
19 more parabolas a& hyperbolas (optional) x
Β 
11 graphs of first degree functions x
11 graphs of first degree functions x11 graphs of first degree functions x
11 graphs of first degree functions x
Β 
9 the basic language of functions x
9 the basic language of functions x9 the basic language of functions x
9 the basic language of functions x
Β 
22 the fundamental theorem of algebra x
22 the fundamental theorem of algebra x22 the fundamental theorem of algebra x
22 the fundamental theorem of algebra x
Β 

Recently uploaded

A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)Gabriella Davis
Β 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Igalia
Β 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
Β 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreternaman860154
Β 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024The Digital Insurer
Β 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
Β 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking MenDelhi Call girls
Β 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
Β 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Enterprise Knowledge
Β 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?Antenna Manufacturer Coco
Β 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfsudhanshuwaghmare1
Β 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonetsnaman860154
Β 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountPuma Security, LLC
Β 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024Rafal Los
Β 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...apidays
Β 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEarley Information Science
Β 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Miguel AraΓΊjo
Β 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsMaria Levchenko
Β 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
Β 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUK Journal
Β 

Recently uploaded (20)

A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)A Domino Admins Adventures (Engage 2024)
A Domino Admins Adventures (Engage 2024)
Β 
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Raspberry Pi 5: Challenges and Solutions in Bringing up an OpenGL/Vulkan Driv...
Β 
🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
Β 
Presentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreterPresentation on how to chat with PDF using ChatGPT code interpreter
Presentation on how to chat with PDF using ChatGPT code interpreter
Β 
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Bajaj Allianz Life Insurance Company - Insurer Innovation Award 2024
Β 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
Β 
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
08448380779 Call Girls In Diplomatic Enclave Women Seeking Men
Β 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
Β 
Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...Driving Behavioral Change for Information Management through Data-Driven Gree...
Driving Behavioral Change for Information Management through Data-Driven Gree...
Β 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
Β 
Boost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdfBoost Fertility New Invention Ups Success Rates.pdf
Boost Fertility New Invention Ups Success Rates.pdf
Β 
How to convert PDF to text with Nanonets
How to convert PDF to text with NanonetsHow to convert PDF to text with Nanonets
How to convert PDF to text with Nanonets
Β 
Breaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path MountBreaking the Kubernetes Kill Chain: Host Path Mount
Breaking the Kubernetes Kill Chain: Host Path Mount
Β 
The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024The 7 Things I Know About Cyber Security After 25 Years | April 2024
The 7 Things I Know About Cyber Security After 25 Years | April 2024
Β 
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Apidays Singapore 2024 - Building Digital Trust in a Digital Economy by Veron...
Β 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
Β 
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Mastering MySQL Database Architecture: Deep Dive into MySQL Shell and MySQL R...
Β 
Handwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed textsHandwritten Text Recognition for manuscripts and early printed texts
Handwritten Text Recognition for manuscripts and early printed texts
Β 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
Β 
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdfUnderstanding Discord NSFW Servers A Guide for Responsible Users.pdf
Understanding Discord NSFW Servers A Guide for Responsible Users.pdf
Β 

Solve Systems of Linear Equations Using Elimination Method (40

  • 1. Systems of Linear Equations
  • 2. Systems of Linear Equations We need one piece of information to solve for one unknown quantity.
  • 3. Systems of Linear Equations We need one piece of information to solve for one unknown quantity. If 2 hamburgers cost 4 dollars and x is the cost of a hamburger, then 2x = 4 or x = $2.
  • 4. Systems of Linear Equations We need one piece of information to solve for one unknown quantity. If 2 hamburgers cost 4 dollars and x is the cost of a hamburger, then 2x = 4 or x = $2. If there are two unknowns x and y, we need two pieces of information to solve them.
  • 5. Systems of Linear Equations We need one piece of information to solve for one unknown quantity. If 2 hamburgers cost 4 dollars and x is the cost of a hamburger, then 2x = 4 or x = $2. If there are two unknowns x and y, we need two pieces of information to solve them. Example A. Let x = cost of a hamburger, y = cost of an order of fries. If two hamburgers and an order of fries cost $7, and one hamburger and one order of fries cost $5. What is the price of each?
  • 6. Systems of Linear Equations We need one piece of information to solve for one unknown quantity. If 2 hamburgers cost 4 dollars and x is the cost of a hamburger, then 2x = 4 or x = $2. If there are two unknowns x and y, we need two pieces of information to solve them. Example A. Let x = cost of a hamburger, y = cost of an order of fries. If two hamburgers and an order of fries cost $7, and one hamburger and one order of fries cost $5. What is the price of each? We translate this information into two equations:
  • 7. Systems of Linear Equations We need one piece of information to solve for one unknown quantity. If 2 hamburgers cost 4 dollars and x is the cost of a hamburger, then 2x = 4 or x = $2. If there are two unknowns x and y, we need two pieces of information to solve them. Example A. Let x = cost of a hamburger, y = cost of an order of fries. If two hamburgers and an order of fries cost $7, and one hamburger and one order of fries cost $5. What is the price of each? 2x + y = 7 We translate this information into two equations:
  • 8. Systems of Linear Equations We need one piece of information to solve for one unknown quantity. If 2 hamburgers cost 4 dollars and x is the cost of a hamburger, then 2x = 4 or x = $2. If there are two unknowns x and y, we need two pieces of information to solve them. Example A. Let x = cost of a hamburger, y = cost of an order of fries. If two hamburgers and an order of fries cost $7, and one hamburger and one order of fries cost $5. What is the price of each? 2x + y = 7 x + y = 5 We translate this information into two equations:
  • 9. Systems of Linear Equations We need one piece of information to solve for one unknown quantity. If 2 hamburgers cost 4 dollars and x is the cost of a hamburger, then 2x = 4 or x = $2. If there are two unknowns x and y, we need two pieces of information to solve them. Example A. Let x = cost of a hamburger, y = cost of an order of fries. If two hamburgers and an order of fries cost $7, and one hamburger and one order of fries cost $5. What is the price of each? 2x + y = 7 x + y = 5{ A group of equations such as this is called a system of equations. Eq. 1 Eq. 2 We translate this information into two equations:
  • 10. Systems of Linear Equations We are to find values for x and for y that will satisfy all equations in the system.
  • 11. Systems of Linear Equations We are to find values for x and for y that will satisfy all equations in the system. Such a set of values is called a solution for the system.
  • 12. Systems of Linear Equations We are to find values for x and for y that will satisfy all equations in the system. Such a set of values is called a solution for the system. To solve the system, we note that the difference in the two orders is one hamburger and the difference in price is $2.
  • 13. Systems of Linear Equations We are to find values for x and for y that will satisfy all equations in the system. Such a set of values is called a solution for the system. To solve the system, we note that the difference in the two orders is one hamburger and the difference in price is $2. So the price of the hamburger must be $2.
  • 14. Systems of Linear Equations We are to find values for x and for y that will satisfy all equations in the system. Such a set of values is called a solution for the system. To solve the system, we note that the difference in the two orders is one hamburger and the difference in price is $2. So the price of the hamburger must be $2. In algebra, we subtract the equations in the system: 2x + y = 7 x + y = 5) Eq. 1 Eq. 2
  • 15. Systems of Linear Equations We are to find values for x and for y that will satisfy all equations in the system. Such a set of values is called a solution for the system. To solve the system, we note that the difference in the two orders is one hamburger and the difference in price is $2. So the price of the hamburger must be $2. In algebra, we subtract the equations in the system: 2x + y = 7 x + y = 5) x = 2 Eq. 1 Eq. 2
  • 16. Systems of Linear Equations We are to find values for x and for y that will satisfy all equations in the system. Such a set of values is called a solution for the system. To solve the system, we note that the difference in the two orders is one hamburger and the difference in price is $2. So the price of the hamburger must be $2. In algebra, we subtract the equations in the system: 2x + y = 7 x + y = 5) x = 2 Eq. 1 Eq. 2 Put x = 2 back into Eq. 2, we get y = 3.
  • 17. Systems of Linear Equations We are to find values for x and for y that will satisfy all equations in the system. Such a set of values is called a solution for the system. To solve the system, we note that the difference in the two orders is one hamburger and the difference in price is $2. So the price of the hamburger must be $2. In algebra, we subtract the equations in the system: 2x + y = 7 x + y = 5) x = 2 Eq. 1 Eq. 2 Put x = 2 back into Eq. 2, we get y = 3. Hence a hamburger is $2 and an order of fries is $3.
  • 18. Systems of Linear Equations We are to find values for x and for y that will satisfy all equations in the system. Such a set of values is called a solution for the system. To solve the system, we note that the difference in the two orders is one hamburger and the difference in price is $2. So the price of the hamburger must be $2. In algebra, we subtract the equations in the system: 2x + y = 7 x + y = 5) x = 2 Eq. 1 Eq. 2 Put x = 2 back into Eq. 2, we get y = 3. Hence a hamburger is $2 and an order of fries is $3. This is called the elimination method - we eliminate variables by adding or subtracting two equations.
  • 19. Elimination method reduces the number of variables in the system one at a time. Systems of Linear Equations
  • 20. Elimination method reduces the number of variables in the system one at a time. The method changes a given system into a smaller system. Systems of Linear Equations
  • 21. Elimination method reduces the number of variables in the system one at a time. The method changes a given system into a smaller system. We do this successively until the solution is clear. Systems of Linear Equations
  • 22. Elimination method reduces the number of variables in the system one at a time. The method changes a given system into a smaller system. We do this successively until the solution is clear. Systems of Linear Equations Example B: Let x = cost of a hamburger, y = cost of an order of fries, z = cost of a soda. 2 hamburgers, 3 fries and 3 soda cost $13. 1 hamburger, 2 fries and 2 soda cost $8. 3 hamburgers, 2 fries, 3 soda cost $13. Find x, y, and z.
  • 23. Elimination method reduces the number of variables in the system one at a time. The method changes a given system into a smaller system. We do this successively until the solution is clear. Systems of Linear Equations We translate the information into a system of three equations with three unknowns. Example B. Let x = cost of a hamburger, y = cost of an order of fries, z = cost of a soda. 2 hamburgers, 3 fries and 3 soda cost $13. 1 hamburger, 2 fries and 2 soda cost $8. 3 hamburgers, 2 fries, 3 soda cost $13. Find x, y, and z.
  • 24. 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 Systems of Linear Equations 2 burgers 3 fries, 3 sodas: $13 1 burger, 2 fries and 2 sodas: $8 3 burgers, 2 fries, 3 sodas: $13
  • 25. 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 Select x to eliminate since there is 1x in E2. Systems of Linear Equations 2 burgers 3 fries, 3 sodas: $13 1 burger, 2 fries and 2 sodas: $8 3 burgers, 2 fries, 3 sodas: $13
  • 26. 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 Select x to eliminate since there is 1x in E2. -2*E 2 + E1: Systems of Linear Equations 2 burgers 3 fries, 3 sodas: $13 1 burger, 2 fries and 2 sodas: $8 3 burgers, 2 fries, 3 sodas: $13
  • 27. 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 Select x to eliminate since there is 1x in E2. -2*E 2 + E1: -2x – 4y – 4z = -16 +) 2x + 3y + 3z = 13 Systems of Linear Equations 2 burgers 3 fries, 3 sodas: $13 1 burger, 2 fries and 2 sodas: $8 3 burgers, 2 fries, 3 sodas: $13
  • 28. 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 Select x to eliminate since there is 1x in E2. -2*E 2 + E1: -2x – 4y – 4z = -16 +) 2x + 3y + 3z = 13 0 – y – z = - 3 Systems of Linear Equations 2 burgers 3 fries, 3 sodas: $13 1 burger, 2 fries and 2 sodas: $8 3 burgers, 2 fries, 3 sodas: $13
  • 29. 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 Select x to eliminate since there is 1x in E2. -2*E 2 + E1: -2x – 4y – 4z = -16 +) 2x + 3y + 3z = 13 0 – y – z = - 3 -3*E 2 + E3: Systems of Linear Equations 2 burgers 3 fries, 3 sodas: $13 1 burger, 2 fries and 2 sodas: $8 3 burgers, 2 fries, 3 sodas: $13
  • 30. 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 Select x to eliminate since there is 1x in E2. -2*E 2 + E1: -2x – 4y – 4z = -16 +) 2x + 3y + 3z = 13 0 – y – z = - 3 -3*E 2 + E3: -3x – 6y – 6z = -24 +) 3x + 2y + 3z = 13 Systems of Linear Equations 2 burgers 3 fries, 3 sodas: $13 1 burger, 2 fries and 2 sodas: $8 3 burgers, 2 fries, 3 sodas: $13
  • 31. 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 Select x to eliminate since there is 1x in E2. -2*E 2 + E1: -2x – 4y – 4z = -16 +) 2x + 3y + 3z = 13 0 – y – z = - 3 -3*E 2 + E3: -3x – 6y – 6z = -24 +) 3x + 2y + 3z = 13 0 – 4y – 3z = -11 Systems of Linear Equations 2 burgers 3 fries, 3 sodas: $13 1 burger, 2 fries and 2 sodas: $8 3 burgers, 2 fries, 3 sodas: $13
  • 32. 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 Select x to eliminate since there is 1x in E2. -2*E 2 + E1: -2x – 4y – 4z = -16 +) 2x + 3y + 3z = 13 0 – y – z = - 3 -3*E 2 + E3: -3x – 6y – 6z = -24 +) 3x + 2y + 3z = 13 0 – 4y – 3z = -11 Group these into a system of two equations with two unknowns. Systems of Linear Equations 2 burgers 3 fries, 3 sodas: $13 1 burger, 2 fries and 2 sodas: $8 3 burgers, 2 fries, 3 sodas: $13
  • 33. 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 Select x to eliminate since there is 1x in E2. -2*E 2 + E1: -2x – 4y – 4z = -16 +) 2x + 3y + 3z = 13 0 – y – z = - 3 -3*E 2 + E3: -3x – 6y – 6z = -24 +) 3x + 2y + 3z = 13 0 – 4y – 3z = -11 Group these into a system of two equations with two unknowns. Systems of Linear Equations Hence we reduced the system to a simpler one. 2 burgers 3 fries, 3 sodas: $13 1 burger, 2 fries and 2 sodas: $8 3 burgers, 2 fries, 3 sodas: $13
  • 34. – y – z = - 3 – 4y – 3z = -11{ Systems of Linear Equations
  • 35. – y – z = - 3 – 4y – 3z = -11{ 4y + 3z = 11 { y + z = 3 Eq.4 Eq. 5 Systems of Linear Equations *(-1)
  • 36. – y – z = - 3 – 4y – 3z = -11{ 4y + 3z = 11 { y + z = 3 Eq.4 Eq. 5 Systems of Linear Equations *(-1) Let's eliminate z.
  • 37. – y – z = - 3 – 4y – 3z = -11{ 4y + 3z = 11 { y + z = 3 Eq.4 Eq. 5 -3*E 4 + E5: Systems of Linear Equations *(-1) Let's eliminate z.
  • 38. – y – z = - 3 – 4y – 3z = -11{ 4y + 3z = 11 { y + z = 3 Eq.4 Eq. 5 -3*E 4 + E5: +) 4y + 3z = 11 -3y – 3z = -9 Systems of Linear Equations *(-1) Let's eliminate z.
  • 39. – y – z = - 3 – 4y – 3z = -11{ 4y + 3z = 11 { y + z = 3 Eq.4 Eq. 5 -3*E 4 + E5: +) 4y + 3z = 11 -3y – 3z = -9 y + 0 = 2 y = 2 Systems of Linear Equations *(-1) Let's eliminate z.
  • 40. – y – z = - 3 – 4y – 3z = -11{ 4y + 3z = 11 { y + z = 3 Eq.4 Eq. 5 -3*E 4 + E5: +) 4y + 3z = 11 -3y – 3z = -9 y + 0 = 2 y = 2 To get z, set 2 for y in E4: Systems of Linear Equations *(-1) Let's eliminate z.
  • 41. – y – z = - 3 – 4y – 3z = -11{ 4y + 3z = 11 { y + z = 3 Eq.4 Eq. 5 -3*E 4 + E5: +) 4y + 3z = 11 -3y – 3z = -9 y + 0 = 2 y = 2 To get z, set 2 for y in E4: 2 + z = 3 οƒ  z = 1 Systems of Linear Equations *(-1) Let's eliminate z.
  • 42. – y – z = - 3 – 4y – 3z = -11{ 4y + 3z = 11 { y + z = 3 Eq.4 Eq. 5 -3*E 4 + E5: +) 4y + 3z = 11 -3y – 3z = -9 y + 0 = 2 y = 2 To get z, set 2 for y in E4: 2 + z = 3 οƒ  z = 1 For x, set 2 for y , set 1 for z in E2: Systems of Linear Equations *(-1) Let's eliminate z.
  • 43. – y – z = - 3 – 4y – 3z = -11{ 4y + 3z = 11 { y + z = 3 Eq.4 Eq. 5 -3*E 4 + E5: +) 4y + 3z = 11 -3y – 3z = -9 y + 0 = 2 y = 2 To get z, set 2 for y in E4: 2 + z = 3 οƒ  z = 1 For x, set 2 for y , set 1 for z in E2: x + 2*2 + 2*1 = 8 οƒ  Systems of Linear Equations *(-1) Let's eliminate z.
  • 44. – y – z = - 3 – 4y – 3z = -11{ 4y + 3z = 11 { y + z = 3 Eq.4 Eq. 5 -3*E 4 + E5: +) 4y + 3z = 11 -3y – 3z = -9 y + 0 = 2 y = 2 To get z, set 2 for y in E4: 2 + z = 3 οƒ  z = 1 For x, set 2 for y , set 1 for z in E2: x + 2*2 + 2*1 = 8 οƒ  x + 6 = 8 οƒ  x = 2 Systems of Linear Equations *(-1) Let's eliminate z.
  • 45. – y – z = - 3 – 4y – 3z = -11{ 4y + 3z = 11 { y + z = 3 Eq.4 Eq. 5 -3*E 4 + E5: +) 4y + 3z = 11 -3y – 3z = -9 y + 0 = 2 y = 2 To get z, set 2 for y in E4: 2 + z = 3 οƒ  z = 1 For x, set 2 for y , set 1 for z in E2: x + 2*2 + 2*1 = 8 οƒ  x + 6 = 8 οƒ  x = 2 Systems of Linear Equations *(-1) Hence the hamburger costs $2, and an order of fries costs $2 and the drink costs $1. Let's eliminate z.
  • 46. A matrix is a rectangular table of numbers. Matrix Notation
  • 47. A matrix is a rectangular table of numbers. For example 5 2 -3 4 -1 0 -1 2 -1 6 -2 3 11 9 -4 Matrix Notation are matrices.
  • 48. A matrix is a rectangular table of numbers. For example 5 2 -3 4 -1 0 -1 2 -1 6 -2 3 11 9 -4 Matrix Notation are matrices. Systems of linear equations can be put into matrices and solved using matrix notation.
  • 49. A matrix is a rectangular table of numbers. For example 5 2 -3 4 -1 0 -1 2 -1 6 -2 3 11 9 -4 Matrix Notation are matrices. Systems of linear equations can be put into matrices and solved using matrix notation. x + 4y = -7 2x – 3y = 8{ For example, the system 1 4 -7 2 -3 8 may be written as the matrix: x y #
  • 50. A matrix is a rectangular table of numbers. For example 5 2 -3 4 -1 0 -1 2 -1 6 -2 3 11 9 -4 Matrix Notation are matrices. Systems of linear equations can be put into matrices and solved using matrix notation. x + 4y = -7 2x – 3y = 8{ For example, the system 1 4 -7 2 -3 8 may be written as the matrix: x y # This is called the augmented matrix for the system.
  • 51. A matrix is a rectangular table of numbers. For example 5 2 -3 4 -1 0 -1 2 -1 6 -2 3 11 9 -4 Matrix Notation are matrices. Systems of linear equations can be put into matrices and solved using matrix notation. x + 4y = -7 2x – 3y = 8{ For example, the system 1 4 -7 2 -3 8 may be written as the matrix: x y # This is called the augmented matrix for the system. Each row of the matrix corresponds to an equation, each column corresponds to a variable and the last column corresponds to numbers.
  • 52. Matrix Notation An augmented matrix can be easily converted back to a system .
  • 53. Matrix Notation An augmented matrix can be easily converted back to a system . For example, the augmented matrix 2 -3 8 1 4 -7 is the system x + 4y = -7{2x – 3y = 8
  • 54. Operations of the equations correspond to operations of rows in the matrices. Matrix Notation An augmented matrix can be easily converted back to a system . 2 -3 8 1 4 -7 is the system x + 4y = -7{2x – 3y = 8 For example, the augmented matrix
  • 55. Operations of the equations correspond to operations of rows in the matrices. Three such operations are important. These are the elementary row operations: Matrix Notation An augmented matrix can be easily converted back to a system . 2 -3 8 1 4 -7 is the system x + 4y = -7{2x – 3y = 8 For example, the augmented matrix
  • 56. Matrix Notation I. Switch two rows. An augmented matrix can be easily converted back to a system . 2 -3 8 1 4 -7 is the system x + 4y = -7{2x – 3y = 8 Operations of the equations correspond to operations of rows in the matrices. Three such operations are important. These are the elementary row operations: For example, the augmented matrix
  • 57. Matrix Notation I. Switch two rows. Switching row i with row j is notated as Ri Rj. An augmented matrix can be easily converted back to a system . 2 -3 8 1 4 -7 is the system x + 4y = -7{2x – 3y = 8 Operations of the equations correspond to operations of rows in the matrices. Three such operations are important. These are the elementary row operations: For example, the augmented matrix
  • 58. Matrix Notation 1 4 -7 2 -3 8 For example, R1 R2 I. Switch two rows. Switching row i with row j is notated as Ri Rj. An augmented matrix can be easily converted back to a system . 2 -3 8 1 4 -7 is the system x + 4y = -7{2x – 3y = 8 Operations of the equations correspond to operations of rows in the matrices. Three such operations are important. These are the elementary row operations: For example, the augmented matrix
  • 59. Matrix Notation 1 4 -7 2 -3 8 For example, R1 R2 2 -3 8 1 4 -7 I. Switch two rows. Switching row i with row j is notated as Ri Rj. An augmented matrix can be easily converted back to a system . 2 -3 8 1 4 -7 is the system x + 4y = -7{2x – 3y = 8 Operations of the equations correspond to operations of rows in the matrices. Three such operations are important. These are the elementary row operations: For example, the augmented matrix
  • 60. Matrix Notation II. Multiply a row by a constant k = 0.
  • 61. Matrix Notation II. Multiply a row by a constant k = 0. Multiply row i by k is notated as k*Ri.
  • 62. Matrix Notation II. Multiply a row by a constant k = 0. Multiply row i by k is notated as k*Ri. 1 4 -7 2 -3 8 -3*R2 For example,
  • 63. Matrix Notation II. Multiply a row by a constant k = 0. Multiply row i by k is notated as k*Ri. 1 4 -7 2 -3 8 -3*R2 1 4 -7 -6 9 -24 For example,
  • 64. III. Add the multiple of a row to another row. Matrix Notation II. Multiply a row by a constant k = 0. Multiply row i by k is notated as k*Ri. 1 4 -7 2 -3 8 -3*R2 1 4 -7 -6 9 -24 For example,
  • 65. III. Add the multiple of a row to another row. k times row i added to row j is notated as β€œk*Ri add οƒ  Rj”. Matrix Notation II. Multiply a row by a constant k = 0. Multiply row i by k is notated as k*Ri. 1 4 -7 2 -3 8 -3*R2 1 4 -7 -6 9 -24 For example,
  • 66. III. Add the multiple of a row to another row. k times row i added to row j is notated as β€œk*Ri add οƒ  Rj”. 1 4 -7 2 -3 8 For example, -2*R1 add οƒ  R2 Matrix Notation II. Multiply a row by a constant k = 0. Multiply row i by k is notated as k*Ri. 1 4 -7 2 -3 8 -3*R2 1 4 -7 -6 9 -24 For example,
  • 67. III. Add the multiple of a row to another row. k times row i added to row j is notated as β€œk*Ri add οƒ  Rj”. 1 4 -7 2 -3 8 For example, -2*R1 add οƒ  R2 -2 -8 14 write a copy of -2*R1 Matrix Notation II. Multiply a row by a constant k = 0. Multiply row i by k is notated as k*Ri. 1 4 -7 2 -3 8 -3*R2 1 4 -7 -6 9 -24 For example,
  • 68. III. Add the multiple of a row to another row. k times row i added to row j is notated as β€œk*Ri add οƒ  Rj”. 1 4 -7 2 -3 8 For example, -2*R1 add οƒ  R2 1 4 -7 0 -11 22 -2 -8 14 write a copy of -2*R1 Matrix Notation II. Multiply a row by a constant k = 0. Multiply row i by k is notated as k*Ri. 1 4 -7 2 -3 8 -3*R2 1 4 -7 -6 9 -24 For example,
  • 69. III. Add the multiple of a row to another row. k times row i added to row j is notated as β€œk*Ri add οƒ  Rj”. 1 4 -7 2 -3 8 For example, -2*R1 add οƒ  R2 1 4 -7 0 -11 22 -2 -8 14 write a copy of -2*R1 Fact: Performing elementary row operations on a matrix does not change the solution of the system. Matrix Notation II. Multiply a row by a constant k = 0. Multiply row i by k is notated as k*Ri. 1 4 -7 2 -3 8 -3*R2 1 4 -7 -6 9 -24 For example,
  • 70. Matrix Notation The elimination method may be carried out with matrix notation.
  • 71. Elimination Method in Matrix Notation: Matrix Notation The elimination method may be carried out with matrix notation.
  • 72. Matrix Notation The elimination method may be carried out with matrix notation. Elimination Method in Matrix Notation: 1. Apply row operations to transform the matrix
  • 73. * * * * * * * * * * * * Row operations Matrix Notation The elimination method may be carried out with matrix notation. Elimination Method in Matrix Notation: 1. Apply row operations to transform the matrix
  • 74. * * * * * * * * * * * * Row operations Matrix Notation The elimination method may be carried out with matrix notation. Elimination Method in Matrix Notation: 1. Apply row operations to transform the matrix to the upper diagonal form where all the entries below the main diagonal (the lower left triangular region) are 0 .
  • 75. * * * * * * * * * * * * Row operations * * * * * * * * * 0 0 0 Matrix Notation The elimination method may be carried out with matrix notation. Elimination Method in Matrix Notation: 1. Apply row operations to transform the matrix to the upper diagonal form where all the entries below the main diagonal (the lower left triangular region) are 0 .
  • 76. * * * * * * * * * * * * Row operations * * * * * * * * * 0 0 0 2. Starting from the bottom row, get the answer for one of the variables. Matrix Notation The elimination method may be carried out with matrix notation. Elimination Method in Matrix Notation: 1. Apply row operations to transform the matrix to the upper diagonal form where all the entries below the main diagonal (the lower left triangular region) are 0 .
  • 77. * * * * * * * * * * * * Row operations * * * * * * * * * 0 0 0 2. Starting from the bottom row, get the answer for one of the variables. Then go up one row, use the solution already obtained to get another answer of another variable. Matrix Notation The elimination method may be carried out with matrix notation. Elimination Method in Matrix Notation: 1. Apply row operations to transform the matrix to the upper diagonal form where all the entries below the main diagonal (the lower left triangular region) are 0 .
  • 78. Elimination Method in Matrix Notation: 1. Apply row operations to transform the matrix to the upper diagonal form where all the entries below the main diagonal (the lower left triangular region) are 0 . * * * * * * * * * * * * Row operations * * * * * * * * * 0 0 0 2. Starting from the bottom row, get the answer for one of the variables. Then go up one row, use the solution already obtained to get another answer of another variable. Repeat the process, working from the bottom row to the top row to extract all solutions. Matrix Notation The elimination method may be carried out with matrix notation.
  • 79. x + 4y = -7 2x – 3y = 8{ Eq. 1 Eq. 2 Example C: Solve using matrix notation: Matrix Notation
  • 80. 1 4 -7 2 -3 8 x + 4y = -7 2x – 3y = 8{ Eq. 1 Eq. 2 Example C: Solve using matrix notation: Put the system into a matrix: Matrix Notation
  • 81. 1 4 -7 2 -3 8 -2*R1 add οƒ  R2 x + 4y = -7 2x – 3y = 8{ Eq. 1 Eq. 2 Example C: Solve using matrix notation: Put the system into a matrix: Matrix Notation
  • 82. 1 4 -7 2 -3 8 -2*R1 add οƒ  R2 -2 -8 14 x + 4y = -7 2x – 3y = 8{ Eq. 1 Eq. 2 Example C: Solve using matrix notation: Put the system into a matrix: Matrix Notation
  • 83. 1 4 -7 2 -3 8 -2*R1 add οƒ  R2 1 4 -7 0 -11 22 -2 -8 14 x + 4y = -7 2x – 3y = 8{ Eq. 1 Eq. 2 Example C: Solve using matrix notation: Put the system into a matrix: Matrix Notation
  • 84. 1 4 -7 2 -3 8 -2*R1 add οƒ  R2 1 4 -7 0 -11 22 -2 -8 14 x + 4y = -7 2x – 3y = 8{ Eq. 1 Eq. 2 Example C: Solve using matrix notation: Put the system into a matrix: Starting from the bottom row: -11y = 22 οƒ  y = -2 Matrix Notation
  • 85. 1 4 -7 2 -3 8 -2*R1 add οƒ  R2 1 4 -7 0 -11 22 -2 -8 14 x + 4y = -7 2x – 3y = 8{ Eq. 1 Eq. 2 Example C: Solve using matrix notation: Put the system into a matrix: Starting from the bottom row: -11y = 22 οƒ  y = -2 Go up one row to R1 and set y = -2: Matrix Notation
  • 86. 1 4 -7 2 -3 8 -2*R1 add οƒ  R2 1 4 -7 0 -11 22 -2 -8 14 x + 4y = -7 2x – 3y = 8{ Eq. 1 Eq. 2 Example C: Solve using matrix notation: Put the system into a matrix: Starting from the bottom row: -11y = 22 οƒ  y = -2 Go up one row to R1 and set y = -2: x + 4y = -7 x + 4(-2) = -7 Matrix Notation
  • 87. 1 4 -7 2 -3 8 -2*R1 add οƒ  R2 1 4 -7 0 -11 22 -2 -8 14 x + 4y = -7 2x – 3y = 8{ Eq. 1 Eq. 2 Example C: Solve using matrix notation: Put the system into a matrix: Starting from the bottom row: -11y = 22 οƒ  y = -2 Go up one row to R1 and set y = -2: x + 4y = -7 x + 4(-2) = -7 οƒ  x = 1 Matrix Notation Hence the solution is {x = 1, y = -2} or as the ordered pair (1, -2).
  • 88. Example D: Solve using matrix notation: 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 Matrix Notation
  • 89. Example D: Solve using matrix notation: 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 2 3 3 13 Put the system into a matrix: 1 2 2 8 3 2 3 13 Matrix Notation
  • 90. Example D: Solve using matrix notation: 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 2 3 3 13 R1 R2 Put the system into a matrix: 1 2 2 8 3 2 3 13 2 3 3 13 1 2 2 8 3 2 3 13 Matrix Notation
  • 91. Example D: Solve using matrix notation: 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 2 3 3 13 R1 R2 -2 -4 -4 -16Put the system into a matrix: 1 2 2 8 3 2 3 13 2 3 3 13 1 2 2 8 3 2 3 13 -2*R1 add R2 Matrix Notation
  • 92. Example D: Solve using matrix notation: 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 2 3 3 13 R1 R2 -2 -4 -4 -16Put the system into a matrix: 1 2 2 8 3 2 3 13 2 3 3 13 1 2 2 8 3 2 3 13 -2*R1 add R2 0 -1 -1 -3 1 2 2 8 3 2 3 13 Matrix Notation
  • 93. Example D: Solve using matrix notation: 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 2 3 3 13 R1 R2 -2 -4 -4 -16Put the system into a matrix: 1 2 2 8 3 2 3 13 2 3 3 13 1 2 2 8 3 2 3 13 -2*R1 add R2 0 -1 -1 -3 1 2 2 8 3 2 3 13 -3* R1 add R3 -3 -6 -6 -24 Matrix Notation
  • 94. Example D: Solve using matrix notation: 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 2 3 3 13 R1 R2 -2 -4 -4 -16Put the system into a matrix: 1 2 2 8 3 2 3 13 2 3 3 13 1 2 2 8 3 2 3 13 -2*R1 add R2 0 -1 -1 -3 1 2 2 8 3 2 3 13 -3* R1 add R3 -3 -6 -6 -24 0 -1 -1 -3 1 2 2 8 0 -4 -3 -11 Matrix Notation
  • 95. Example D: Solve using matrix notation: 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 2 3 3 13 R1 R2 -2 -4 -4 -16Put the system into a matrix: 1 2 2 8 3 2 3 13 2 3 3 13 1 2 2 8 3 2 3 13 -2*R1 add R2 0 -1 -1 -3 1 2 2 8 3 2 3 13 -3* R1 add R3 -3 -6 -6 -24 0 -1 -1 -3 1 2 2 8 0 -4 -3 -11 -4*R2 add R3 0 4 4 12 Matrix Notation
  • 96. Example D: Solve using matrix notation: 2x + 3y + 3z = 13 x + 2y + 2z = 8 3x + 2y + 3z = 13 { E 1 E 2 E 3 2 3 3 13 R1 R2 -2 -4 -4 -16Put the system into a matrix: 1 2 2 8 3 2 3 13 2 3 3 13 1 2 2 8 3 2 3 13 -2*R1 add R2 0 -1 -1 -3 1 2 2 8 3 2 3 13 -3* R1 add R3 -3 -6 -6 -24 0 -1 -1 -3 1 2 2 8 0 -4 -3 -11 -4*R2 add R3 0 4 4 12 0 -1 -1 -3 1 2 2 8 0 0 1 1 Matrix Notation
  • 97. 0 -1 -1 -3 1 2 2 8 0 0 1 1 Matrix Notation Extract the solution starting from the bottom row.
  • 98. 0 -1 -1 -3 1 2 2 8 0 0 1 1 From R3, we get z = 1. Matrix Notation Extract the solution starting from the bottom row.
  • 99. 0 -1 -1 -3 1 2 2 8 0 0 1 1 From R3, we get z = 1. Go up one row to R2, we get -y – z = -3 -y – (1) = -3 Matrix Notation Extract the solution starting from the bottom row.
  • 100. 0 -1 -1 -3 1 2 2 8 0 0 1 1 From R3, we get z = 1. Go up one row to R2, we get -y – z = -3 -y – (1) = -3 3 – 1 = y 2 = y Matrix Notation Extract the solution starting from the bottom row.
  • 101. 0 -1 -1 -3 1 2 2 8 0 0 1 1 From R3, we get z = 1. Go up one row to R2, we get -y – z = -3 -y – (1) = -3 3 – 1 = y 2 = y Up to R1, we get x + 2y + 2z = 8 x + 2(2) + 2(1) = 8 Matrix Notation Extract the solution starting from the bottom row.
  • 102. 0 -1 -1 -3 1 2 2 8 0 0 1 1 From R3, we get z = 1. Go up one row to R2, we get -y – z = -3 -y – (1) = -3 3 – 1 = y 2 = y Up to R1, we get x + 2y + 2z = 8 x + 2(2) + 2(1) = 8 x + 6 = 8 x = 2 Matrix Notation Extract the solution starting from the bottom row.
  • 103. 0 -1 -1 -3 1 2 2 8 0 0 1 1 From R3, we get z = 1. Go up one row to R2, we get -y – z = -3 -y – (1) = -3 3 – 1 = y 2 = y Up to R1, we get x + 2y + 2z = 8 x + 2(2) + 2(1) = 8 x + 6 = 8 x = 2 So the solution is (2, 2, 1). Matrix Notation Extract the solution starting from the bottom row.
  • 104. A soda costs $1, a hot dog costs $3 and an ice cream costs $2. Find the cost of the following orders. 1) 2 sodas, 2 hotdogs and 1 ice cream. ______ 2) 3 sodas, 3 hotdogs and 2 ice creams. ______ 3) 4 sodas, 6 hotdogs and no ice creams. ______ 4) 8 sodas, 6 hotdogs and 7 ice creams. ______ Now let a soda cost $x, a hot dog cost $y and an ice cream cost $z. Find an algebraic expression for the cost of the above orders. 5) _______________ 6) _____________ 7) _____________ 8) _____________ 9) If order #1 is $15, order #2 is $24 and order #3 is $32, write the system of equations and solve. 10) If order #1 is $17, order #3 is $36 and order #4 is $67, write the system of equations and solve. Systems of Linear Equations
  • 105.
  • 106. 1) $10 3) $22 5) 2x +2y + z 7) 4x + 6y 9) 2x + 2y + z = $15 3x + 3y + 2z = $24 4x + 6y = $32. x = 2, y = 4, z = 3 Systems of Linear Equations 11) x + 2y = 7 4y = 8 x = 3, y = 2 13) x + 2y + 4z = 3 y + z = 4 z = 6 x = -17, y = -2, z =6 13) 2 1 1 0 -2.5 7.5 17) -1 2 2 1 1 1 1 2 2 2 1 1 (Answers to the odd problems)