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Matrices & Determinants
Chapter: 1
Matrices & Determinants
Matrices & Determinants
Session Objectives
• Meaning of matrix
• Type of matrices
• Transpose of Matrix
• Meaning of symmetric and skew symmetric
matrices
• Minor & co-factors
• Computation of adjoint and inverse of a
matrix
Matrices & Determinants
TYPES OF MATRICES
NAME DESCRIPTION EXAMPLE
Rectangular
matrix
No. of rows is not equal to
no. of columns
Square matrix No. of rows is equal to no. of
columns
Diagonal
matrix
Non-zero element in principal
diagonal and zero in all other
positions
Scalar matrix Diagonal matrix in which all
the elements on principal
diagonal and same








5
0
2
1
2
6

2 1 3
2 0 1
1 2 4




















7
0
0
0
4
0
0
0
2










4
0
0
0
4
0
0
0
4
Matrices & Determinants
TYPES OF MATRICES
NAME DESCRIPTION EXAMPLE
Row matrix A matrix with only 1
row
Column matrix A matrix with only I
column
Identity matrix Diagonal matrix
having each
diagonal element
equal to one (I)
Zero matrix A matrix with all zero
entries

3 2 14
 

2
3












1
0
0
1
0 0
0 0






Matrices & Determinants
TYPES OF MATRICES
NAME DESCRIPTION EXAMPLE
Upper Triangular
matrix
Square matrix
having all the entries
zero below the
principal diagonal
Lower Triangular
matrix
Square matrix
having all the entries
zero above the
principal diagonal










7
0
0
6
4
0
3
5
2










7
3
6
0
4
5
0
0
2
Matrices & Determinants
Determinants
If is a square matrix of order 1,
then |A| = | a11 | = a11
ij
A = a
 
 
If is a square matrix of order 2, then
11 12
21 22
a a
A =
a a
 
 
 
|A| = = a11a22 – a21a12
a a
a a
1
1 1
2
2
1 2
2
Matrices & Determinants
Example
4 - 3
Evaluate the determinant :
2 5
 
4 - 3
Solution : = 4 ×5 - 2 × -3 = 20 + 6 = 26
2 5
Matrices & Determinants
Solution
If A = is a square matrix of order 3, then
11 12 13
21 22 23
31 32 33
a a a
a a a
a a a
 
 
 
 
 
[Expanding along first row]
11 12 13
22 23 21 23 21 22
21 22 23 11 12 13
32 33 31 33 31 32
31 32 33
a a a
a a a a a a
| A |= a a a = a - a + a
a a a a a a
a a a
     
11 22 33 32 23 12 21 33 31 23 13 21 32 31 22
= a a a - a a - a a a - a a + a a a - a a
   
11 22 33 12 31 23 13 21 32 11 23 32 12 21 33 13 31 22
a a a a a a a a a a a a a a a a a a
     
Matrices & Determinants
Example
2 3 - 5
Evaluate the determinant : 7 1 - 2
-3 4 1
 
2 3 - 5
1 - 2 7 - 2 7 1
7 1 - 2 = 2 - 3 + -5
4 1 -3 1 -3 4
-3 4 1
     
= 2 1 + 8 - 3 7 - 6 - 5 28 + 3
= 18 - 3 - 155
= -140
[Expanding along first row]
Solution :
Matrices & Determinants
Minors
-1 4
If A = , then
2 3
 
 
 
21 21 22 22
M = Minor of a = 4, M = Minor of a = -1
11 11 12 12
M = Minor of a = 3, M = Minor of a = 2
Matrices & Determinants
Minors
4 7 8
If A = -9 0 0 , then
2 3 4
 
 
 
 
 
M11 = Minor of a11 = determinant of the order 2 × 2 square
sub-matrix is obtained by leaving first
row and first column of A
0 0
= = 0
3 4
Similarly, M23 = Minor of a23
4 7
= =12-14=-2
2 3
M32 = Minor of a32 etc.
4 8
= = 0+72 = 72
-9 0
Matrices & Determinants
Cofactors
 i+j
ij ij ij
C = Cofactor of a in A = -1 M ,
ij ij
where M is minor of a in A
Matrices & Determinants
Cofactors (Con.)
C11 = Cofactor of a11 = (–1)1 + 1 M11 = (–1)1 +1
0 0
= 0
3 4
C23 = Cofactor of a23 = (–1)2 + 3 M23 =  
4 7
2
2 3
C32 = Cofactor of a32 = (–1)3 + 2M32 = etc.
4 8
- = -72
-9 0
4 7 8
A = -9 0 0
2 3 4
 
 
 
 
 
Matrices & Determinants
Value of Determinant in Terms
of Minors and Cofactors
11 12 13
21 22 23
31 32 33
a a a
If A = a a a , then
a a a
 
 
 
 
 
 
3 3
i j
ij ij ij ij
j 1 j 1
A 1 a M a C

 
  
 
i1 i1 i2 i2 i3 i3
= a C +a C +a C , for i =1 or i =2 or i =3
Matrices & Determinants
Properties of Determinants
1. The value of a determinant remains unchanged, if its
rows and columns are interchanged.
1 1 1 1 2 3
2 2 2 1 2 3
3 3 3 1 2 3
a b c a a a
a b c = b b b
a b c c c c
i e A A

. . '
2. If any two rows (or columns) of a determinant are interchanged,
then the value of the determinant is changed by minus sign.
 
1 1 1 2 2 2
2 2 2 1 1 1 2 1
3 3 3 3 3 3
a b c a b c
a b c = - a b c R R
a b c a b c
Applying 
Matrices & Determinants
Properties (Con.)
3. If all the elements of a row (or column) is multiplied by a
non-zero number k, then the value of the new determinant
is k times the value of the original determinant.
1 1 1 1 1 1
2 2 2 2 2 2
3 3 3 3 3 3
ka kb kc a b c
a b c = k a b c
a b c a b c
which also implies
1 1 1 1 1 1
2 2 2 2 2 2
3 3 3 3 3 3
a b c ma mb mc
1
a b c = a b c
m
a b c a b c
Matrices & Determinants
Properties (Con.)
4. If each element of any row (or column) consists of
two or more terms, then the determinant can be
expressed as the sum of two or more determinants.
1 1 1 1 1 1 1 1
2 2 2 2 2 2 2 2
3 3 3 3 3 3 3 3
a +x b c a b c x b c
a +y b c = a b c + y b c
a +z b c a b c z b c
5. The value of a determinant is unchanged, if any row
(or column) is multiplied by a number and then added
to any other row (or column).
 
1 1 1 1 1 1 1 1
2 2 2 2 2 2 2 2 1 1 2 3
3 3 3 3 3 3 3 3
a b c a +mb - nc b c
a b c = a +mb - nc b c C C + mC -nC
a b c a +mb - nc b c
Applying 
Matrices & Determinants
Properties (Con.)
6. If any two rows (or columns) of a determinant are
identical, then its value is zero.
2 2 2
3 3 3
0 0 0
a b c = 0
a b c
7. If each element of a row (or column) of a determinant is zero,
then its value is zero.
1 1 1
2 2 2
1 1 1
a b c
a b c = 0
a b c
Matrices & Determinants
Properties (Con.)
 
a 0 0
8 Let A = 0 b 0 be a diagonal matrix, then
0 0 c
 
 
 
 
 
a 0 0
= 0 b 0
0 0 c
A abc

Matrices & Determinants
Row(Column) Operations
Following are the notations to evaluate a determinant:
Similar notations can be used to denote column
operations by replacing R with C.
(i) Ri to denote ith row
(ii) Ri Rj to denote the interchange of ith and jth
rows.
(iii) Ri Ri + lRj to denote the addition of l times the
elements of jth row to the corresponding elements
of ith row.
(iv) lRi to denote the multiplication of all elements of
ith row by l.


Matrices & Determinants
Evaluation of Determinants
If a determinant becomes zero on putting
is the factor of the determinant.
 
x = , then x -
 
2
3
x 5 2
For example, if Δ = x 9 4 , then at x =2
x 16 8
, because C1 and C2 are identical at x = 2
Hence, (x – 2) is a factor of determinant .
  0

Matrices & Determinants
Sign System for Expansion of
Determinant
Sign System for order 2 and order 3 are
given by
+ – +
+ –
, – + –
– +
+ – +
Matrices & Determinants
 
42 1 6 6×7 1 6
i 28 7 4 = 4×7 7 4
14 3 2 2×7 3 2
 
1
6 1 6
=7 4 7 4 Taking out 7 common from C
2 3 2
Example-1
6 -3 2
2 -1 2
-10 5 2
42 1 6
28 7 4
14 3 2
Find the value of the following determinants
(i) (ii)
Solution :
1 3
= 7 × 0 C and C are identical
= 0
 
 
Matrices & Determinants
Example –1 (ii)
6 -3 2
2 -1 2
-10 5 2
(ii)
 
 
 
   
    
 
3 2 3 2
1 2 1 2
5 2 5 2
 
    
 
 
    
 

1
1 2
3 3 2
( 2) 1 1 2 Taking out 2 common from C
5 5 2
( 2) 0 C and C are identical
0
Matrices & Determinants
Evaluate the determinant
1 a b+c
1 b c+a
1 c a+b
Solution :
 
3 2 3
1 a b+c 1 a a+b+c
1 b c+a = 1 b a+b+c Applying c c +c
1 c a+b 1 c a+b+c

    3
1 a 1
= a+b+c 1 b 1 Taking a+b+c common from C
1 c 1
 
 
Example - 2
  1 3
= a+b + c ×0 C and C are identical
= 0
 
 
Matrices & Determinants
2 2 2
a b c
We have a b c
bc ca ab
 
2
1 1 2 2 2 3
(a-b) b-c c
= (a-b)(a+b) (b-c)(b+c) c Applying C C -C and C C -C
-c(a-b) -a(b-c) ab
 
   
2
1 2
1 1 c
Taking a-b and b-c common
=(a-b)(b-c) a+b b+c c
from C and C respectively
-c -a ab
 
 
 
Example - 3
bc
2 2 2
a b c
a b c
ca ab
Evaluate the determinant:
Solution:
Matrices & Determinants
 
2
1 1 2
0 1 c
=(a-b)(b-c) -(c-a) b+c c Applying c c -c
-(c-a) -a ab

2
0 1 c
=-(a-b)(b-c)(c-a) 1 b+c c
1 -a ab
 
2
2 2 3
0 1 c
= -(a-b)(b-c)(c-a) 0 a+b+c c -ab Applying R R -R
1 -a ab

Now expanding along C1 , we get
(a-b) (b-c) (c-a) [- (c2 – ab – ac – bc – c2)]
= (a-b) (b-c) (c-a) (ab + bc + ac)
Solution Cont.
Matrices & Determinants
Without expanding the determinant,
prove that
3
3x+y 2x x
4x+3y 3x 3x =x
5x+6y 4x 6x
3x+y 2x x 3x 2x x y 2x x
L.H.S= 4x+3y 3x 3x = 4x 3x 3x + 3y 3x 3x
5x+6y 4x 6x 5x 4x 6x 6y 4x 6x
3 2
3 2 1 1 2 1
= x 4 3 3 +x y 3 3 3
5 4 6 6 4 6
Example-4
Solution :
 
3 2
1 2
3 2 1
= x 4 3 3 +x y×0 C and C are identical in II determinant
5 4 6
Matrices & Determinants
Solution Cont.
 
3
1 1 2
1 2 1
= x 1 3 3 Applying C C -C
1 4 6

 
3
2 2 1 3 3 2
1 2 1
=x 0 1 2 ApplyingR R -R and R R -R
0 1 3
 
 
3
1
3
= x ×(3-2) Expanding along C
=x = R.H.S.
3
3 2 1
=x 4 3 3
5 4 6
Matrices & Determinants
Prove that : = 0 , where wis cube root of unity.
3 5
3 4
5 5
1 ω ω
ω 1 ω
ω ω 1
3 5 3 3 2
3 4 3 3
5 5 3 2 3 2
1 ω ω 1 ω ω .ω
L.H.S = ω 1 ω = ω 1 ω .ω
ω ω 1 ω .ω ω .ω 1
 
2
3
2 2
1 2
1 1 ω
= 1 1 ω ω =1
ω ω 1
=0=R.H.S. C and C are identical
 
 
Example -5
Solution :
Matrices & Determinants
Example-6
2
x+a b c
a x+b c =x (x+a+b+c)
a b x+C
Prove that :
 
1 1 2 3
x+a b c x+a+b+c b c
L.H.S= a x+b c = x+a+b+c x+b c
a b x+C x+a+b+c b x+c
Applying C C +C +C

Solution :
 
  1
1 b c
= x+a+b+c 1 x+b c
1 b x+c
Taking x+a+b+c commonfrom C
 
 
Matrices & Determinants
Solution cont.
 
2 2 1 3 3 1
1 b c
=(x+a+b+c) 0 x 0
0 0 x
Applying R R -R and R R -R
 
Expanding along C1 , we get
(x + a + b + c) [1(x2)] = x2 (x + a + b + c)
= R.H.S
Matrices & Determinants
 
1 1 2 3
2(a+b+c) 2(a+b+c) 2(a+b+c)
= c+a a+b b+c Applying R R +R +R
a+b b+c c+a

1 1 1
=2(a+b+c) c+a a+b b+c
a+b b+c c+a
Example -7
Solution :
Using properties of determinants, prove that
2 2 2
b+c c+a a+b
c+a a+b b+c =2(a+b+c)(ab+bc+ca-a -b -c ).
a+b b+c c+a
b+c c+a a+b
L.H.S= c+a a+b b+c
a+b b+c c+a
Matrices & Determinants
 
1 1 2 2 2 3
0 0 1
=2(a+b+c)(c-b) (a-c) b+c Applying C C -C and C C -C
(a-c) (b-a) c+a
 
Now expanding along R1 , we get
2
2(a+b+c) (c-b)(b-a)-(a-c)
 
 
2 2 2
=2(a+b+c) bc -b - ac+ab-(a +c -2ac)
 
 
Solution Cont.
2 2 2
=2(a+b+c) ab+bc+ac-a -b -c
=R.H.S
 
 
Matrices & Determinants
Using properties of determinants prove that
2
x+4 2x 2x
2x x+4 2x =(5x+4)(4-x)
2x 2x x+4
Example - 8
1 2x 2x
=(5x+4)1 x+4 2x
1 2x x+4
Solution :
 
1 1 2 3
x+4 2x 2x 5x+4 2x 2x
L.H.S= 2x x+4 2x =5x+4 x+4 2x Applying C C +C +C
2x 2x x+4 5x+4 2x x+4

Matrices & Determinants
Solution Cont.
 
2 2 1 3 3 2
1 2x 2x
=(5x+4) 0 -(x-4) 0 ApplyingR R -R and R R -R
0 x-4 -(x-4)
 
Now expanding along C1 , we get
2
(5x+4) 1(x- 4) -0
 
 
2
=(5x+4)(4-x)
=R.H.S
Matrices & Determinants
Example -9
Using properties of determinants, prove that
x+9 x x
x x+9 x =243 (x+3)
x x x+9
x+9 x x
L.H.S= x x+9 x
x x x+9
 
1 1 2 3
3x+9 x x
= 3x+9 x+9 x Applying C C +C +C
3x+9 x x+9

Solution :
Matrices & Determinants
 
1
=3(x+3) 81 Expanding along C
=243(x+3)
=R.H.S.

1 x x
=(3x+9)1 x+9 x
1 x x+9
Solution Cont.
  2 2 1 3 3 2
1 x x
=3 x+3 0 9 0 Applying R R -R and R R -R
0 -9 9
 
 
 
Matrices & Determinants
Example -10
Solution :
2 2 2 2 2
2 2 2 2 2
1 1 3
2 2 2 2 2
(b+c) a bc b +c a bc
L.H.S.= (c+a) b ca = c +a b ca Applying C C -2C
(a+b) c ab a +b c ab
 

 
 
2 2 2 2
2 2 2 2
1 1 2
2 2 2 2
a +b +c a bc
a +b +c b ca Applying C C +C
a +b +c c ab
 
2
2 2 2 2
2
1 a bc
=(a +b +c )1 b ca
1 c ab
2 2
2 2 2 2 2
2 2
(b+c) a bc
(c+a) b ca =(a +b +c )(a-b)(b-c)(c-a)(a+b+c)
(a+b) c ab
Show that
Matrices & Determinants
Solution Cont.
 
2
2 2 2
2 2 1 3 3 2
1 a bc
=(a +b +c ) 0 (b-a)(b+a) c(a-b) Applying R R -R and R R -R
0 (c-b)(c+b) a(b-c)
 
 
2 2 2 2 2
1
=(a +b +c )(a-b)(b-c)(-ab-a +bc+c ) Expanding along C
2 2 2
=(a +b +c )(a-b)(b-c)(c-a)(a+b+c)=R.H.S.
2
2 2 2
1 a bc
=(a +b +c )(a-b)(b-c) 0 -(b+a) c
0 -(b+c) a
    
2 2 2
=(a +b +c )(a-b)(b-c) b c-a + c-a c+a
 
 
Matrices & Determinants
Applications of Determinants
(Area of a Triangle)
The area of a triangle whose vertices are
is given by the expression
1 1 2 2 3 3
(x , y ), (x , y ) and (x , y )
1 1
2 2
3 3
x y 1
1
Δ= x y 1
2
x y 1
1 2 3 2 3 1 3 1 2
1
= [x (y - y ) + x (y - y ) + x (y - y )]
2
Matrices & Determinants
Example
Find the area of a triangle whose
vertices are (-1, 8), (-2, -3) and (3, 2).
Solution :
1 1
2 2
3 3
x y 1 -1 8 1
1 1
Area of triangle= x y 1 = -2 -3 1
2 2
x y 1 3 2 1
 
1
= -1(-3-2)-8(-2-3)+1(-4+9)
2
 
1
= 5+40+5 =25 sq.units
2
Matrices & Determinants
Condition of Collinearity of
Three Points
If are three points,
then A, B, C are collinear
1 1 2 2 3 3
A (x , y ), B (x , y ) and C (x , y )
1 1 1 1
2 2 2 2
3 3 3 3
Area of triangle ABC =0
x y 1 x y 1
1
x y 1 =0 x y 1 =0
2
x y 1 x y 1

 
Matrices & Determinants
If the points (x, -2) , (5, 2), (8, 8) are collinear,
find x , using determinants.
Example
Solution :
x -2 1
5 2 1 =0
8 8 1

      
x 2-8 - -2 5-8 +1 40-16 =0

-6x-6+24=0

6x=18 x=3
 
Since the given points are collinear.
Matrices & Determinants
Solution of System of 2 Linear
Equations (Cramer’s Rule)
Let the system of linear equations be
 
2 2 2
a x+b y = c ... ii
 
1 1 1
a x+b y = c ... i
1 2
D D
Then x = , y = provided D 0,
D D

1 1 1 1 1 1
1 2
2 2 2 2 2 2
a b c b a c
where D = , D = and D =
a b c b a c
Matrices & Determinants
Cramer’s Rule (Con.)
then the system is consistent and has infinitely many
solutions.
  1 2
2 If D = 0 and D = D = 0,
then the system is inconsistent and has no solution.
 
1 If D 0
Note :
,

then the system is consistent and has unique solution.
  1 2
3 If D=0 and one of D , D 0,

Matrices & Determinants
Example
2 -3
D= =2+9=11 0
3 1

1
7 -3
D = =7+15=22
5 1
2
2 7
D = =10-21=-11
3 5
Solution :
1 2
D 0
D D
22 -11
By Cramer's Rule x= = =2 and y= = =-1
D 11 D 11


Using Cramer's rule , solve the following
system of equations 2x-3y=7, 3x+y=5
Matrices & Determinants
Solution of System of 3 Linear
Equations (Cramer’s Rule)
Let the system of linear equations be
 
2 2 2 2
a x+b y+c z = d ... ii
 
1 1 1 1
a x+b y+c z = d ... i
 
3 3 3 3
a x+b y+c z = d ... iii
3
1 2 D
D D
Then x = , y = z = provided D 0,
D D D
, 
1 1 1 1 1 1 1 1 1
2 2 2 1 2 2 2 2 2 2 2
3 3 3 3 3 3 3 3 3
a b c d b c a d c
where D = a b c , D = d b c , D = a d c
a b c d b c a d c
1 1 1
3 2 2 2
3 3 3
a b d
and D = a b d
a b d
Matrices & Determinants
Cramer’s Rule (Con.)
Note:
(1) If D  0, then the system is consistent and has a unique
solution.
(2) If D=0 and D1 = D2 = D3 = 0, then the system has infinite
solutions or no solution.
(3) If D = 0 and one of D1, D2, D3  0, then the system
is inconsistent and has no solution.
(4) If d1 = d2 = d3 = 0, then the system is called the system of
homogeneous linear equations.
(i) If D  0, then the system has only trivial solution x = y = z = 0.
(ii) If D = 0, then the system has infinite solutions.
Matrices & Determinants
Example
Using Cramer's rule , solve the following
system of equations
5x - y+ 4z = 5
2x + 3y+ 5z = 2
5x - 2y + 6z = -1
Solution :
5 -1 4
D= 2 3 5
5 -2 6
1
5 -1 4
D = 2 3 5
-1 -2 6
= 5(18+10)+1(12+5)+4(-4 +3)
= 140 +17 –4
= 153
= 5(18+10) + 1(12-25)+4(-4 -15)
= 140 –13 –76 =140 - 89
= 51 0

Matrices & Determinants
3
5 -1 5
D = 2 3 2
5 -2 -1
= 5(-3 +4)+1(-2 - 10)+5(-4-15)
= 5 – 12 – 95 = 5 - 107
= - 102
Solution Cont.
1 2
3
D 0
D D
153 102
By Cramer's Rule x = = =3, y = = =2
D 51 D 51
D -102
and z= = =-2
D 51


2
5 5 4
D = 2 2 5
5 -1 6
= 5(12 +5)+5(12 - 25)+ 4(-2 - 10)
= 85 + 65 – 48 = 150 - 48
= 102
Matrices & Determinants
Example
Solve the following system of homogeneous linear equations:
x + y – z = 0, x – 2y + z = 0, 3x + 6y + -5z = 0
Solution:
     
1 1 - 1
We have D = 1 - 2 1 = 1 10 - 6 - 1 -5 - 3 - 1 6 + 6
3 6 - 5
= 4 + 8 - 12 = 0
 
 
 
 
 
The systemhas infinitely many solutions.

Putting z = k, in first two equations, we get
x + y = k, x – 2y = -k
Matrices & Determinants
Solution (Con.)
1
k 1
D -k - 2 -2k + k k
By Cramer's rule x = = = =
D -2 - 1 3
1 1
1 - 2

2
1 k
D 1 - k -k - k 2k
y = = = =
D -2 - 1 3
1 1
1 - 2
k 2k
x = , y = , z = k , where k R
3 3
 
These values of x, y and z = k satisfy (iii) equation.
Matrices & Determinants
Thank you

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chp-1-matrices-determinants1.ppt

  • 1. Matrices & Determinants Chapter: 1 Matrices & Determinants
  • 2. Matrices & Determinants Session Objectives • Meaning of matrix • Type of matrices • Transpose of Matrix • Meaning of symmetric and skew symmetric matrices • Minor & co-factors • Computation of adjoint and inverse of a matrix
  • 3. Matrices & Determinants TYPES OF MATRICES NAME DESCRIPTION EXAMPLE Rectangular matrix No. of rows is not equal to no. of columns Square matrix No. of rows is equal to no. of columns Diagonal matrix Non-zero element in principal diagonal and zero in all other positions Scalar matrix Diagonal matrix in which all the elements on principal diagonal and same         5 0 2 1 2 6  2 1 3 2 0 1 1 2 4                     7 0 0 0 4 0 0 0 2           4 0 0 0 4 0 0 0 4
  • 4. Matrices & Determinants TYPES OF MATRICES NAME DESCRIPTION EXAMPLE Row matrix A matrix with only 1 row Column matrix A matrix with only I column Identity matrix Diagonal matrix having each diagonal element equal to one (I) Zero matrix A matrix with all zero entries  3 2 14    2 3             1 0 0 1 0 0 0 0      
  • 5. Matrices & Determinants TYPES OF MATRICES NAME DESCRIPTION EXAMPLE Upper Triangular matrix Square matrix having all the entries zero below the principal diagonal Lower Triangular matrix Square matrix having all the entries zero above the principal diagonal           7 0 0 6 4 0 3 5 2           7 3 6 0 4 5 0 0 2
  • 6. Matrices & Determinants Determinants If is a square matrix of order 1, then |A| = | a11 | = a11 ij A = a     If is a square matrix of order 2, then 11 12 21 22 a a A = a a       |A| = = a11a22 – a21a12 a a a a 1 1 1 2 2 1 2 2
  • 7. Matrices & Determinants Example 4 - 3 Evaluate the determinant : 2 5   4 - 3 Solution : = 4 ×5 - 2 × -3 = 20 + 6 = 26 2 5
  • 8. Matrices & Determinants Solution If A = is a square matrix of order 3, then 11 12 13 21 22 23 31 32 33 a a a a a a a a a           [Expanding along first row] 11 12 13 22 23 21 23 21 22 21 22 23 11 12 13 32 33 31 33 31 32 31 32 33 a a a a a a a a a | A |= a a a = a - a + a a a a a a a a a a       11 22 33 32 23 12 21 33 31 23 13 21 32 31 22 = a a a - a a - a a a - a a + a a a - a a     11 22 33 12 31 23 13 21 32 11 23 32 12 21 33 13 31 22 a a a a a a a a a a a a a a a a a a      
  • 9. Matrices & Determinants Example 2 3 - 5 Evaluate the determinant : 7 1 - 2 -3 4 1   2 3 - 5 1 - 2 7 - 2 7 1 7 1 - 2 = 2 - 3 + -5 4 1 -3 1 -3 4 -3 4 1       = 2 1 + 8 - 3 7 - 6 - 5 28 + 3 = 18 - 3 - 155 = -140 [Expanding along first row] Solution :
  • 10. Matrices & Determinants Minors -1 4 If A = , then 2 3       21 21 22 22 M = Minor of a = 4, M = Minor of a = -1 11 11 12 12 M = Minor of a = 3, M = Minor of a = 2
  • 11. Matrices & Determinants Minors 4 7 8 If A = -9 0 0 , then 2 3 4           M11 = Minor of a11 = determinant of the order 2 × 2 square sub-matrix is obtained by leaving first row and first column of A 0 0 = = 0 3 4 Similarly, M23 = Minor of a23 4 7 = =12-14=-2 2 3 M32 = Minor of a32 etc. 4 8 = = 0+72 = 72 -9 0
  • 12. Matrices & Determinants Cofactors  i+j ij ij ij C = Cofactor of a in A = -1 M , ij ij where M is minor of a in A
  • 13. Matrices & Determinants Cofactors (Con.) C11 = Cofactor of a11 = (–1)1 + 1 M11 = (–1)1 +1 0 0 = 0 3 4 C23 = Cofactor of a23 = (–1)2 + 3 M23 =   4 7 2 2 3 C32 = Cofactor of a32 = (–1)3 + 2M32 = etc. 4 8 - = -72 -9 0 4 7 8 A = -9 0 0 2 3 4          
  • 14. Matrices & Determinants Value of Determinant in Terms of Minors and Cofactors 11 12 13 21 22 23 31 32 33 a a a If A = a a a , then a a a             3 3 i j ij ij ij ij j 1 j 1 A 1 a M a C         i1 i1 i2 i2 i3 i3 = a C +a C +a C , for i =1 or i =2 or i =3
  • 15. Matrices & Determinants Properties of Determinants 1. The value of a determinant remains unchanged, if its rows and columns are interchanged. 1 1 1 1 2 3 2 2 2 1 2 3 3 3 3 1 2 3 a b c a a a a b c = b b b a b c c c c i e A A  . . ' 2. If any two rows (or columns) of a determinant are interchanged, then the value of the determinant is changed by minus sign.   1 1 1 2 2 2 2 2 2 1 1 1 2 1 3 3 3 3 3 3 a b c a b c a b c = - a b c R R a b c a b c Applying 
  • 16. Matrices & Determinants Properties (Con.) 3. If all the elements of a row (or column) is multiplied by a non-zero number k, then the value of the new determinant is k times the value of the original determinant. 1 1 1 1 1 1 2 2 2 2 2 2 3 3 3 3 3 3 ka kb kc a b c a b c = k a b c a b c a b c which also implies 1 1 1 1 1 1 2 2 2 2 2 2 3 3 3 3 3 3 a b c ma mb mc 1 a b c = a b c m a b c a b c
  • 17. Matrices & Determinants Properties (Con.) 4. If each element of any row (or column) consists of two or more terms, then the determinant can be expressed as the sum of two or more determinants. 1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 a +x b c a b c x b c a +y b c = a b c + y b c a +z b c a b c z b c 5. The value of a determinant is unchanged, if any row (or column) is multiplied by a number and then added to any other row (or column).   1 1 1 1 1 1 1 1 2 2 2 2 2 2 2 2 1 1 2 3 3 3 3 3 3 3 3 3 a b c a +mb - nc b c a b c = a +mb - nc b c C C + mC -nC a b c a +mb - nc b c Applying 
  • 18. Matrices & Determinants Properties (Con.) 6. If any two rows (or columns) of a determinant are identical, then its value is zero. 2 2 2 3 3 3 0 0 0 a b c = 0 a b c 7. If each element of a row (or column) of a determinant is zero, then its value is zero. 1 1 1 2 2 2 1 1 1 a b c a b c = 0 a b c
  • 19. Matrices & Determinants Properties (Con.)   a 0 0 8 Let A = 0 b 0 be a diagonal matrix, then 0 0 c           a 0 0 = 0 b 0 0 0 c A abc 
  • 20. Matrices & Determinants Row(Column) Operations Following are the notations to evaluate a determinant: Similar notations can be used to denote column operations by replacing R with C. (i) Ri to denote ith row (ii) Ri Rj to denote the interchange of ith and jth rows. (iii) Ri Ri + lRj to denote the addition of l times the elements of jth row to the corresponding elements of ith row. (iv) lRi to denote the multiplication of all elements of ith row by l.  
  • 21. Matrices & Determinants Evaluation of Determinants If a determinant becomes zero on putting is the factor of the determinant.   x = , then x -   2 3 x 5 2 For example, if Δ = x 9 4 , then at x =2 x 16 8 , because C1 and C2 are identical at x = 2 Hence, (x – 2) is a factor of determinant .   0 
  • 22. Matrices & Determinants Sign System for Expansion of Determinant Sign System for order 2 and order 3 are given by + – + + – , – + – – + + – +
  • 23. Matrices & Determinants   42 1 6 6×7 1 6 i 28 7 4 = 4×7 7 4 14 3 2 2×7 3 2   1 6 1 6 =7 4 7 4 Taking out 7 common from C 2 3 2 Example-1 6 -3 2 2 -1 2 -10 5 2 42 1 6 28 7 4 14 3 2 Find the value of the following determinants (i) (ii) Solution : 1 3 = 7 × 0 C and C are identical = 0    
  • 24. Matrices & Determinants Example –1 (ii) 6 -3 2 2 -1 2 -10 5 2 (ii)                  3 2 3 2 1 2 1 2 5 2 5 2                    1 1 2 3 3 2 ( 2) 1 1 2 Taking out 2 common from C 5 5 2 ( 2) 0 C and C are identical 0
  • 25. Matrices & Determinants Evaluate the determinant 1 a b+c 1 b c+a 1 c a+b Solution :   3 2 3 1 a b+c 1 a a+b+c 1 b c+a = 1 b a+b+c Applying c c +c 1 c a+b 1 c a+b+c      3 1 a 1 = a+b+c 1 b 1 Taking a+b+c common from C 1 c 1     Example - 2   1 3 = a+b + c ×0 C and C are identical = 0    
  • 26. Matrices & Determinants 2 2 2 a b c We have a b c bc ca ab   2 1 1 2 2 2 3 (a-b) b-c c = (a-b)(a+b) (b-c)(b+c) c Applying C C -C and C C -C -c(a-b) -a(b-c) ab       2 1 2 1 1 c Taking a-b and b-c common =(a-b)(b-c) a+b b+c c from C and C respectively -c -a ab       Example - 3 bc 2 2 2 a b c a b c ca ab Evaluate the determinant: Solution:
  • 27. Matrices & Determinants   2 1 1 2 0 1 c =(a-b)(b-c) -(c-a) b+c c Applying c c -c -(c-a) -a ab  2 0 1 c =-(a-b)(b-c)(c-a) 1 b+c c 1 -a ab   2 2 2 3 0 1 c = -(a-b)(b-c)(c-a) 0 a+b+c c -ab Applying R R -R 1 -a ab  Now expanding along C1 , we get (a-b) (b-c) (c-a) [- (c2 – ab – ac – bc – c2)] = (a-b) (b-c) (c-a) (ab + bc + ac) Solution Cont.
  • 28. Matrices & Determinants Without expanding the determinant, prove that 3 3x+y 2x x 4x+3y 3x 3x =x 5x+6y 4x 6x 3x+y 2x x 3x 2x x y 2x x L.H.S= 4x+3y 3x 3x = 4x 3x 3x + 3y 3x 3x 5x+6y 4x 6x 5x 4x 6x 6y 4x 6x 3 2 3 2 1 1 2 1 = x 4 3 3 +x y 3 3 3 5 4 6 6 4 6 Example-4 Solution :   3 2 1 2 3 2 1 = x 4 3 3 +x y×0 C and C are identical in II determinant 5 4 6
  • 29. Matrices & Determinants Solution Cont.   3 1 1 2 1 2 1 = x 1 3 3 Applying C C -C 1 4 6    3 2 2 1 3 3 2 1 2 1 =x 0 1 2 ApplyingR R -R and R R -R 0 1 3     3 1 3 = x ×(3-2) Expanding along C =x = R.H.S. 3 3 2 1 =x 4 3 3 5 4 6
  • 30. Matrices & Determinants Prove that : = 0 , where wis cube root of unity. 3 5 3 4 5 5 1 ω ω ω 1 ω ω ω 1 3 5 3 3 2 3 4 3 3 5 5 3 2 3 2 1 ω ω 1 ω ω .ω L.H.S = ω 1 ω = ω 1 ω .ω ω ω 1 ω .ω ω .ω 1   2 3 2 2 1 2 1 1 ω = 1 1 ω ω =1 ω ω 1 =0=R.H.S. C and C are identical     Example -5 Solution :
  • 31. Matrices & Determinants Example-6 2 x+a b c a x+b c =x (x+a+b+c) a b x+C Prove that :   1 1 2 3 x+a b c x+a+b+c b c L.H.S= a x+b c = x+a+b+c x+b c a b x+C x+a+b+c b x+c Applying C C +C +C  Solution :     1 1 b c = x+a+b+c 1 x+b c 1 b x+c Taking x+a+b+c commonfrom C    
  • 32. Matrices & Determinants Solution cont.   2 2 1 3 3 1 1 b c =(x+a+b+c) 0 x 0 0 0 x Applying R R -R and R R -R   Expanding along C1 , we get (x + a + b + c) [1(x2)] = x2 (x + a + b + c) = R.H.S
  • 33. Matrices & Determinants   1 1 2 3 2(a+b+c) 2(a+b+c) 2(a+b+c) = c+a a+b b+c Applying R R +R +R a+b b+c c+a  1 1 1 =2(a+b+c) c+a a+b b+c a+b b+c c+a Example -7 Solution : Using properties of determinants, prove that 2 2 2 b+c c+a a+b c+a a+b b+c =2(a+b+c)(ab+bc+ca-a -b -c ). a+b b+c c+a b+c c+a a+b L.H.S= c+a a+b b+c a+b b+c c+a
  • 34. Matrices & Determinants   1 1 2 2 2 3 0 0 1 =2(a+b+c)(c-b) (a-c) b+c Applying C C -C and C C -C (a-c) (b-a) c+a   Now expanding along R1 , we get 2 2(a+b+c) (c-b)(b-a)-(a-c)     2 2 2 =2(a+b+c) bc -b - ac+ab-(a +c -2ac)     Solution Cont. 2 2 2 =2(a+b+c) ab+bc+ac-a -b -c =R.H.S    
  • 35. Matrices & Determinants Using properties of determinants prove that 2 x+4 2x 2x 2x x+4 2x =(5x+4)(4-x) 2x 2x x+4 Example - 8 1 2x 2x =(5x+4)1 x+4 2x 1 2x x+4 Solution :   1 1 2 3 x+4 2x 2x 5x+4 2x 2x L.H.S= 2x x+4 2x =5x+4 x+4 2x Applying C C +C +C 2x 2x x+4 5x+4 2x x+4 
  • 36. Matrices & Determinants Solution Cont.   2 2 1 3 3 2 1 2x 2x =(5x+4) 0 -(x-4) 0 ApplyingR R -R and R R -R 0 x-4 -(x-4)   Now expanding along C1 , we get 2 (5x+4) 1(x- 4) -0     2 =(5x+4)(4-x) =R.H.S
  • 37. Matrices & Determinants Example -9 Using properties of determinants, prove that x+9 x x x x+9 x =243 (x+3) x x x+9 x+9 x x L.H.S= x x+9 x x x x+9   1 1 2 3 3x+9 x x = 3x+9 x+9 x Applying C C +C +C 3x+9 x x+9  Solution :
  • 38. Matrices & Determinants   1 =3(x+3) 81 Expanding along C =243(x+3) =R.H.S.  1 x x =(3x+9)1 x+9 x 1 x x+9 Solution Cont.   2 2 1 3 3 2 1 x x =3 x+3 0 9 0 Applying R R -R and R R -R 0 -9 9      
  • 39. Matrices & Determinants Example -10 Solution : 2 2 2 2 2 2 2 2 2 2 1 1 3 2 2 2 2 2 (b+c) a bc b +c a bc L.H.S.= (c+a) b ca = c +a b ca Applying C C -2C (a+b) c ab a +b c ab        2 2 2 2 2 2 2 2 1 1 2 2 2 2 2 a +b +c a bc a +b +c b ca Applying C C +C a +b +c c ab   2 2 2 2 2 2 1 a bc =(a +b +c )1 b ca 1 c ab 2 2 2 2 2 2 2 2 2 (b+c) a bc (c+a) b ca =(a +b +c )(a-b)(b-c)(c-a)(a+b+c) (a+b) c ab Show that
  • 40. Matrices & Determinants Solution Cont.   2 2 2 2 2 2 1 3 3 2 1 a bc =(a +b +c ) 0 (b-a)(b+a) c(a-b) Applying R R -R and R R -R 0 (c-b)(c+b) a(b-c)     2 2 2 2 2 1 =(a +b +c )(a-b)(b-c)(-ab-a +bc+c ) Expanding along C 2 2 2 =(a +b +c )(a-b)(b-c)(c-a)(a+b+c)=R.H.S. 2 2 2 2 1 a bc =(a +b +c )(a-b)(b-c) 0 -(b+a) c 0 -(b+c) a      2 2 2 =(a +b +c )(a-b)(b-c) b c-a + c-a c+a    
  • 41. Matrices & Determinants Applications of Determinants (Area of a Triangle) The area of a triangle whose vertices are is given by the expression 1 1 2 2 3 3 (x , y ), (x , y ) and (x , y ) 1 1 2 2 3 3 x y 1 1 Δ= x y 1 2 x y 1 1 2 3 2 3 1 3 1 2 1 = [x (y - y ) + x (y - y ) + x (y - y )] 2
  • 42. Matrices & Determinants Example Find the area of a triangle whose vertices are (-1, 8), (-2, -3) and (3, 2). Solution : 1 1 2 2 3 3 x y 1 -1 8 1 1 1 Area of triangle= x y 1 = -2 -3 1 2 2 x y 1 3 2 1   1 = -1(-3-2)-8(-2-3)+1(-4+9) 2   1 = 5+40+5 =25 sq.units 2
  • 43. Matrices & Determinants Condition of Collinearity of Three Points If are three points, then A, B, C are collinear 1 1 2 2 3 3 A (x , y ), B (x , y ) and C (x , y ) 1 1 1 1 2 2 2 2 3 3 3 3 Area of triangle ABC =0 x y 1 x y 1 1 x y 1 =0 x y 1 =0 2 x y 1 x y 1   
  • 44. Matrices & Determinants If the points (x, -2) , (5, 2), (8, 8) are collinear, find x , using determinants. Example Solution : x -2 1 5 2 1 =0 8 8 1         x 2-8 - -2 5-8 +1 40-16 =0  -6x-6+24=0  6x=18 x=3   Since the given points are collinear.
  • 45. Matrices & Determinants Solution of System of 2 Linear Equations (Cramer’s Rule) Let the system of linear equations be   2 2 2 a x+b y = c ... ii   1 1 1 a x+b y = c ... i 1 2 D D Then x = , y = provided D 0, D D  1 1 1 1 1 1 1 2 2 2 2 2 2 2 a b c b a c where D = , D = and D = a b c b a c
  • 46. Matrices & Determinants Cramer’s Rule (Con.) then the system is consistent and has infinitely many solutions.   1 2 2 If D = 0 and D = D = 0, then the system is inconsistent and has no solution.   1 If D 0 Note : ,  then the system is consistent and has unique solution.   1 2 3 If D=0 and one of D , D 0, 
  • 47. Matrices & Determinants Example 2 -3 D= =2+9=11 0 3 1  1 7 -3 D = =7+15=22 5 1 2 2 7 D = =10-21=-11 3 5 Solution : 1 2 D 0 D D 22 -11 By Cramer's Rule x= = =2 and y= = =-1 D 11 D 11   Using Cramer's rule , solve the following system of equations 2x-3y=7, 3x+y=5
  • 48. Matrices & Determinants Solution of System of 3 Linear Equations (Cramer’s Rule) Let the system of linear equations be   2 2 2 2 a x+b y+c z = d ... ii   1 1 1 1 a x+b y+c z = d ... i   3 3 3 3 a x+b y+c z = d ... iii 3 1 2 D D D Then x = , y = z = provided D 0, D D D ,  1 1 1 1 1 1 1 1 1 2 2 2 1 2 2 2 2 2 2 2 3 3 3 3 3 3 3 3 3 a b c d b c a d c where D = a b c , D = d b c , D = a d c a b c d b c a d c 1 1 1 3 2 2 2 3 3 3 a b d and D = a b d a b d
  • 49. Matrices & Determinants Cramer’s Rule (Con.) Note: (1) If D  0, then the system is consistent and has a unique solution. (2) If D=0 and D1 = D2 = D3 = 0, then the system has infinite solutions or no solution. (3) If D = 0 and one of D1, D2, D3  0, then the system is inconsistent and has no solution. (4) If d1 = d2 = d3 = 0, then the system is called the system of homogeneous linear equations. (i) If D  0, then the system has only trivial solution x = y = z = 0. (ii) If D = 0, then the system has infinite solutions.
  • 50. Matrices & Determinants Example Using Cramer's rule , solve the following system of equations 5x - y+ 4z = 5 2x + 3y+ 5z = 2 5x - 2y + 6z = -1 Solution : 5 -1 4 D= 2 3 5 5 -2 6 1 5 -1 4 D = 2 3 5 -1 -2 6 = 5(18+10)+1(12+5)+4(-4 +3) = 140 +17 –4 = 153 = 5(18+10) + 1(12-25)+4(-4 -15) = 140 –13 –76 =140 - 89 = 51 0 
  • 51. Matrices & Determinants 3 5 -1 5 D = 2 3 2 5 -2 -1 = 5(-3 +4)+1(-2 - 10)+5(-4-15) = 5 – 12 – 95 = 5 - 107 = - 102 Solution Cont. 1 2 3 D 0 D D 153 102 By Cramer's Rule x = = =3, y = = =2 D 51 D 51 D -102 and z= = =-2 D 51   2 5 5 4 D = 2 2 5 5 -1 6 = 5(12 +5)+5(12 - 25)+ 4(-2 - 10) = 85 + 65 – 48 = 150 - 48 = 102
  • 52. Matrices & Determinants Example Solve the following system of homogeneous linear equations: x + y – z = 0, x – 2y + z = 0, 3x + 6y + -5z = 0 Solution:       1 1 - 1 We have D = 1 - 2 1 = 1 10 - 6 - 1 -5 - 3 - 1 6 + 6 3 6 - 5 = 4 + 8 - 12 = 0           The systemhas infinitely many solutions.  Putting z = k, in first two equations, we get x + y = k, x – 2y = -k
  • 53. Matrices & Determinants Solution (Con.) 1 k 1 D -k - 2 -2k + k k By Cramer's rule x = = = = D -2 - 1 3 1 1 1 - 2  2 1 k D 1 - k -k - k 2k y = = = = D -2 - 1 3 1 1 1 - 2 k 2k x = , y = , z = k , where k R 3 3   These values of x, y and z = k satisfy (iii) equation.