In the previous section, we completed a discussion on multiplication of matrices. In this section, we will see transpose of a matrix.
Transpose of a Matrix
This can be written in 9 steps:
1. Suppose that, we are given a matrix A.
• Based on A, we can write a new matrix A' in such a way that:
♦ Rows in A, are the columns in A'.
♦ Columns in A, are the rows in A'.
2. In other words,
♦ First row of A, becomes the first column in A'.
♦ Second row of A, becomes the second column in A'.
♦ Third row of A, becomes the third column in A'.
♦ so on . . .
3. This is same as:
♦ First column of A, becomes the first row in A'.
♦ Second column of A, becomes the second row in A'.
♦ Third column of A, becomes the third row in A'.
♦ so on . . .
4. Let us see an example:
If A = $\left[\begin{array}{r}
-7 &{ 0 } \\
8 &{ \sqrt{2} } \\
-{\frac{1}{3}} &{ 3 } \\
\end{array}\right]
$, then A' = $\left[\begin{array}{r}
-7 &{ 8 } &{ -{\frac{1}{3}} } \\
0 &{ \sqrt{2} } &{ 3 } \\
\end{array}\right]
$
5. Consider any element, say $-{\frac{1}{3}}$ in A. It’s position is: row 3, column 1.
• But in A', the position of $-{\frac{1}{3}}$ is: row 1, column 3.
♦ That is., the row and column are interchanged.
6. This interchanging of rows and columns is applicable to all elements in general.
• We can write:
♦ In the original matrix, an element is at position i,j.
♦ Then in the new matrix, that element will be at the position j,i.
7. Also note that:
If the order of the original matrix is m×n, then the order of the new matrix will be n×m.
8. Based on the above steps, we can write the definition:
If A = [aij]m×n, then A' = [aji]n×m .
9. The new matrix A' is called the transpose of A. It can be denoted either as A' or AT.
Properties of transpose of matrices
• We have to be familiar with four properties:
For any matrices A and B of suitable orders, we have
I. (A')' = A II. (kA)' = kA' (where k is any constant)
III. (A+B)' = A' + B' IV. (AB)' = B' A'.
[We mention ‘suitable orders’ because, any two given matrices cannot be added or multiplied. If we want (A+B), then A and B must be of the same order. Similarly, if we want (AB), then number of columns in A must be equal to the number of rows in B]
• We will see the proofs of the four properties in higher classes. At present, we will verify them using examples.
Let A = $\left[\begin{array}{r}
9 &{ 6 } &{ -4 }\\
0 &{ \sqrt{2} } &{ 1 }\\
\end{array}\right]
$ and B = $\left[\begin{array}{r}
-1 &{ 2 } &{ 5 }\\
11 &{ 7 } &{ 3 }\\
\end{array}\right] $.
1. Verifying property I:
2. Verifying property II:
• From (4) and (6), we get:
(kB)' = kB' (where k is any constant)
3. Verifying property III:
• From (5) and (7), we get:
(A+B)' = A' + B'
4. Verifying property IV:
Let X = $\left[\begin{array}{r}
9 &{ 6 } &{ -4 }\\
0 &{ {2} } &{ 1 }\\
\end{array}\right]
$ and Y = $\left[\begin{array}{r}
-1 &{ 2 } &{ 5 }\\
11 &{ 7 } &{ 3 }\\
7 &{ 1 } &{ 4 }\\
\end{array}\right] $.
• From (3) and (7), we get:
(XY)' = Y' X'
(note that, positions of X and Y are interchanged)
In the next section, we will see symmetric and skew symmetric matrices.
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