1. Solving Systems of Equations and Inequalities
Section Two variable linear equations
Section Three variable linear equations
Section 2.3 Matrices Resolution of linear systems
Section Determinants & Inverses of Matrices
Section 2.6 Solving Systems of Linear Inequalities
Section Linear Programming

2. Section 2.1 Two Variable Linear Equations
A set of two or more linear equations that each contain two variables.
These equations represent lines that will intersect, overlap, or be parallel to each other.

3. Section 2.1 Two Variable Linear Equations
When these lines intersect or overlap each other they are said to be consistent. This means they have at least one point of intersection. If there is only one point of intersection, the lines are independent. If there is more than one point of intersection, the lines are dependent.
When two lines do not intersect, they are said to be inconsistent because the lines are parallel.

4. Section 2.1 Two Variable Linear Equations
Check your understanding:
Given the following two linear equations, determine the consistency & dependence of the system. 2x + y = 5 & 4x + 2y = 8
Consistent, independent
Consistent, dependent
Inconsistent

5. Section 2.1 Two Variable Linear Equations
Check your understanding:
Given the following two linear equations, determine the consistency & dependence of the system. 2x + y = 5 & 4x + 2y = 8
Consistent, independent
Consistent, dependent
Inconsistent

6. Section 2.1 Two Variable Linear Equations
Check your understanding:
Given the following two linear equations, determine the consistency & dependence of the system. 3x + 2y = 5 & 6x + 2y = 8
Consistent, independent
Consistent, dependent
Inconsistent

7. Section 2.1 Two Variable Linear Equations
Check your understanding:
Given the following two linear equations, determine the consistency & dependence of the system. 3x + 2y = 5 & 6x + 2y = 8
Consistent, independent
Consistent, dependent
Inconsistent

8. Section 2.1 Two Variable Linear Equations
Systems of two linear equations are usually solved using either the elimination method or the substitution method.
The elimination method uses a process of removing one of the two variables simultaneously from both equations through addition of equal but opposite coefficients.
In blue we have y = 3x - 2, and in red we have y = -x + 2.

9. Section 2.1 Two Variable Linear Equations
In blue we have y = 3x - 2, and in red we have y = -x + 2.
Blue 3x – y = 2
Red x + y = 2
4x = 4
With the variable y having equal but opposite values we can add the two equations together and eliminate the y variable. We get 4x = 4. This allows x = 1, and by inserting x = 1 back into the equation we can see that y = 1.

10. Section 2.1 Two Variable Linear Equations
The substitution method uses a process of rewriting one of the two equations by isolating one of the variables and then substituting the equation into the other equation.
In blue we have y = 3x - 2, and in red we have y = -x + 2.
With both equations in the form of y equals, we can substitute the 2nd equation into the first and we get: -x + 2 = 3x – 2. Solving for x we get -4x = -4 and x = 1.

11. Section 2.1 Two Variable Linear Equations
Check your understanding:
Given the following two linear equations, use the substitution method to start the solution of the system.
5x + 3y = x + 2y = 20
Y = 10 – 6x
Y = 10 – 3x
Y = x

12. Section 2.1 Two Variable Linear Equations
Check your understanding:
Given the following two linear equations, use the substitution method to start the solution of the system.
5x + 3y = x + 2y = 20
Y = 10 – 6x
Y = 10 – 3x
Y = x

13. Section 2.2 Three variable linear systems
Three linear equation systems are solved using the elimination and substitution methods.
The technique requires the isolation of one of the variables amongst the three equations.
This gets repeated for a 2nd variable and the remaining variable is then determined.
Afterwards, the other variables are determined.

14. Section 2.2 Three variable linear systems
Sample
X + 2y + 2z = 10
2x – y + 2z = 6
X – 3y + 2z = 1
Solve for x, y,& z.
Isolate the z value first. Combine line 1 & 2 and then combine line 3 & 2.
X + 2y + 2z = 10  X + 2y + 2z = 10
2x – y + 2z = 6 x +y – 2z = x + 3y = 4
X – 3y + 2z = 1  X – 3y + 2z = 1
2x – y + 2z = 6  x +y – 2z = x - 2y = -5

15. Section 2.2 Three variable linear systems
Sample
X + 2y + 2z = 10
2x – y + 2z = 6
X – 3y + 2z = 1
Solve for x, y,& z.
Isolate the x value next. Combine line 1 & 2 answer and the line 3 & 2 answer.
X + 2y + 2z = 11  X + 2y + 2z = 11
2x – y + 2z = 6  x +y – 2z = x + 3y = 5
X – 3y + 2z = 1  X – 3y + 2z = 1
2x – y + 2z = 6  x +y – 2z = x - 2y = -5
-x + 3y = 5  -x + 3y = 5
-x -2y = -5  x + 2y = 5
5y = 10
Y = 2, x = 1
Solve for z by reinserting y & x values (2) + 2z = 10
Z = 2.5

16. Section Matrices
Matrix – A rectangle array of terms (elements) arranged in columns and rows. A matrix with m rows and n columns is called an m x n matrix, (read m by n matrix).
Matrices are also used to determine solutions for multiple variable linear equations. This technique can be used as an alternative to elimination or substitution methods.

17. Section 2.3 - Matrices = a11 a12 a13 a21 a22 a23 a31 a32 a33
3 x 3 Matrix
The first number indicates the row (horizontal) and the second number indicates the column number (vertical).
Equal Matrices – Two matrices are equal if and only they have the same dimensions and are equal element by element.
This expression states that
Y = 2x – 6 and x = 2y. Using the substitution method, we see that
Y = 2(2y) – 6 and so y = 2, x = 4. Y X
2x – 6 2y =

18. Section 2.3 - Matrices = = = =
Addition of Matrices – The sum of two m x n matrices is a m x n matrix in which the elements are the sum of the corresponding elements of the given matrices. =
Solve for A + B. = B A
-2 + (-6) (-1)
(-3) =
A + B =
A + B

19. Section 2.3 - Matrices = = = =
Subtraction of Matrices – The difference of two m x n matrices is equal to the sum A + (-B) where (-B) is the additive inverse of B. =
Solve for A - B. = B A
-2 - (-6) (-1)
(-3) =
A - B =
A - B

20. Section 2.3 - Matrices = = = =
Scalar Product – The product of a scalar k and an m x n matrix A is an m x n matrix denoted by kA. Each element of kA equals k times the corresponding element of A. =
Solve for kA. = k 5 A
5(-2) 5(0 ) 5(1)
5(0) 5(5) 5(-8) = kA = kA

21. Section 2.5 Determinants and Inverses
A determinant is a square array of numbers (written within a pair of vertical lines) which represents a certain sum of products.
Calculating a 2 × 2 Determinant
In general, we find the value of a 2 × 2 determinant with elements a, b, c, d as follows:
We multiply the diagonals (top left × bottom right first), (bottom left x top right) then subtract the first product minus the second.
a b
c d
det =
ad - cb

22. Cramer’s Rule
Cramer’s Rule begins with the solving of the determinant for the system followed by the determinants for each of the variables within the system.
The determinant for each of the variables is calculated by first substituting the solution column values for the variable column values and then worked on as a 2 x 2 matrix.

23. Cramer’s Rule (continued)

24. Cramer’s Rule (conclusion)