For AI agents: use /llms.txt for the Nakafa content index.
A matrix transpose is formed by swapping rows and columns. If entry aij is in row and column of , the same entry is in row and column of .
The transpose of A is written as AT or A′. If A has dimensions m×n, then AT has dimensions n×m and satisfies (AT)ji=aij.
To obtain the matrix transpose, follow these steps:
- Write the first row of the original matrix as the first column of the transpose matrix.
- Write the second row of the original matrix as the second column of the transpose matrix.
- Continue this process for all rows in the original matrix.
Suppose we have matrix A:
Then, the transpose of matrix A is:
Notice how the first row [ab] becomes
the first column [ab], and
the second row [cd] becomes
the second column [cd].
Given matrix B with order 2×3:
The transpose of matrix B, denoted BT, will have order 3×2:
- The first row of B ([123]) becomes the first column of BT.
- The second row of B ([456]) becomes the second column of .
If C is a column matrix:
Then its transpose, CT, is a row matrix:
Given a square matrix D:
Then its transpose, DT, is also a square matrix:
The transpose satisfies the following identities:
- (AT)T=A (The transpose of a transpose matrix is the
matrix itself)
- (A+B)T=AT+BT (Transpose of the sum of two matrices)
- (A−B)T=AT−BT (Transpose of the subtraction of
two matrices)
- (kA)T=kAT, where k is a
scalar
- (AB)T=BTAT (Transpose of the product of two matrices,
note the reversed order)
Determine the transpose of the following matrices and state the type of the resulting matrix (e.g., row matrix, column matrix, square matrix).
-
A=[13−5]
-
B=931−105
-
C=2143651−2−7
-
AT=13−5
The single row of A becomes a single column. Thus, AT has order 3×1 and is a column matrix.
-
BT=[9−13015]
-
CT=23116−245−7
Published: . Updated: .
Each row of B becomes a column of BT. The dimensions change from 3×2 to 2×3, so the result is a rectangular matrix.
Reading the columns of C as the rows of CT gives the matrix above. Its order remains 3×3, so it is still a square matrix.