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 β 4y β 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 β 4y β 4z = -16
+) 2x + 3y + 3z = 13
0 β y β 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 β 4y β 4z = -16
+) 2x + 3y + 3z = 13
0 β y β 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 β 4y β 4z = -16
+) 2x + 3y + 3z = 13
0 β y β z = - 3
-3*E 2 + E3:
-3x β 6y β 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 β 4y β 4z = -16
+) 2x + 3y + 3z = 13
0 β y β z = - 3
-3*E 2 + E3:
-3x β 6y β 6z = -24
+) 3x + 2y + 3z = 13
0 β 4y β 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 β 4y β 4z = -16
+) 2x + 3y + 3z = 13
0 β y β z = - 3
-3*E 2 + E3:
-3x β 6y β 6z = -24
+) 3x + 2y + 3z = 13
0 β 4y β 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 β 4y β 4z = -16
+) 2x + 3y + 3z = 13
0 β y β z = - 3
-3*E 2 + E3:
-3x β 6y β 6z = -24
+) 3x + 2y + 3z = 13
0 β 4y β 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. β y β z = - 3
β 4y β 3z = -11{
Systems of Linear Equations
35. β y β z = - 3
β 4y β 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
Systems of Linear Equations
*(-1)
36. β y β z = - 3
β 4y β 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
Systems of Linear Equations
*(-1)
Let's eliminate z.
37. β y β z = - 3
β 4y β 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. β y β z = - 3
β 4y β 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y β 3z = -9
Systems of Linear Equations
*(-1)
Let's eliminate z.
39. β y β z = - 3
β 4y β 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y β 3z = -9
y + 0 = 2
y = 2
Systems of Linear Equations
*(-1)
Let's eliminate z.
40. β y β z = - 3
β 4y β 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y β 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. β y β z = - 3
β 4y β 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y β 3z = -9
y + 0 = 2
y = 2
To get z, set 2 for y in E4: 2 + z = 3 ο z = 1
Systems of Linear Equations
*(-1)
Let's eliminate z.
42. β y β z = - 3
β 4y β 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y β 3z = -9
y + 0 = 2
y = 2
To get z, set 2 for y in E4: 2 + z = 3 ο z = 1
For x, set 2 for y , set 1 for z in E2:
Systems of Linear Equations
*(-1)
Let's eliminate z.
43. β y β z = - 3
β 4y β 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y β 3z = -9
y + 0 = 2
y = 2
To get z, set 2 for y in E4: 2 + z = 3 ο z = 1
For x, set 2 for y , set 1 for z in E2:
x + 2*2 + 2*1 = 8 ο
Systems of Linear Equations
*(-1)
Let's eliminate z.
44. β y β z = - 3
β 4y β 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y β 3z = -9
y + 0 = 2
y = 2
To get z, set 2 for y in E4: 2 + z = 3 ο z = 1
For x, set 2 for y , set 1 for z in E2:
x + 2*2 + 2*1 = 8 ο x + 6 = 8 ο x = 2
Systems of Linear Equations
*(-1)
Let's eliminate z.
45. β y β z = - 3
β 4y β 3z = -11{ 4y + 3z = 11
{ y + z = 3 Eq.4
Eq. 5
-3*E 4 + E5:
+) 4y + 3z = 11
-3y β 3z = -9
y + 0 = 2
y = 2
To get z, set 2 for y in E4: 2 + z = 3 ο z = 1
For x, set 2 for y , set 1 for z in E2:
x + 2*2 + 2*1 = 8 ο x + 6 = 8 ο 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 β 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 β 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 β 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.
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 β 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 β 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 β 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 β 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 β 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 β 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 β 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
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 βk*Ri add ο Rjβ.
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 βk*Ri add ο Rjβ.
1 4 -7
2 -3 8
For example,
-2*R1 add ο 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 βk*Ri add ο Rjβ.
1 4 -7
2 -3 8
For example,
-2*R1 add ο 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 βk*Ri add ο Rjβ.
1 4 -7
2 -3 8
For example,
-2*R1 add ο 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 βk*Ri add ο Rjβ.
1 4 -7
2 -3 8
For example,
-2*R1 add ο 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,
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 β 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 β 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 ο R2
x + 4y = -7
2x β 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 ο R2
-2 -8 14
x + 4y = -7
2x β 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 ο R2 1 4 -7
0 -11 22
-2 -8 14
x + 4y = -7
2x β 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 ο R2 1 4 -7
0 -11 22
-2 -8 14
x + 4y = -7
2x β 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 ο y = -2
Matrix Notation
85. 1 4 -7
2 -3 8
-2*R1 add ο R2 1 4 -7
0 -11 22
-2 -8 14
x + 4y = -7
2x β 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 ο y = -2
Go up one row to R1 and set y = -2:
Matrix Notation
86. 1 4 -7
2 -3 8
-2*R1 add ο R2 1 4 -7
0 -11 22
-2 -8 14
x + 4y = -7
2x β 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 ο 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 ο R2 1 4 -7
0 -11 22
-2 -8 14
x + 4y = -7
2x β 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 ο y = -2
Go up one row to R1 and set y = -2:
x + 4y = -7
x + 4(-2) = -7 ο 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
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 β z = -3
-y β (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 β z = -3
-y β (1) = -3
3 β 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 β z = -3
-y β (1) = -3
3 β 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 β z = -3
-y β (1) = -3
3 β 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 β z = -3
-y β (1) = -3
3 β 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)