You have a table of a shopkeeper's prices arranged as a matrix. Suddenly every price must be doubled for a festival, or cut to 90% in a sale. You don't want to touch each number one by one — you want a single instruction: multiply the whole matrix by a number. That number is called a scalar, and the operation is scalar multiplication.
The Idea
To multiply a matrix A by a scalar k, you multiply every entry of A by k. Nothing else changes — the order (size) of the matrix stays exactly the same.
If A=[aij]m×n and k is a real number, then
kA=[kaij]m×n
An Example
A=[20−14],3A=[3⋅23⋅03⋅(−1)3⋅4]=[60−312]
A negative scalar flips every sign. In particular −A=(−1)A, which is exactly the matrix you use to subtract: A−B=A+(−1)B.
Properties (all inherited from ordinary numbers)
For scalars k,l and matrices A,B of the same order:
Scalar multiplication of a matrix scales each row by that scalar, so the determinant scales by (scalar)order. For a 3×3 matrix A, ∣3A∣=27∣A∣.
The key idea here is how the determinant behaves when you multiply a matrix by a constant. Many students rush and think ∣3A∣=3∣A∣, but that’s only true for a 1×1 matrix. For larger matrices, the scalar multiplies every row, and the determinant picks up a factor from each row.
Think of it this way: if you take a 3×3 matrix A and multiply it by 3, you are multiplying each of its three rows by 3. The determinant is a multilinear function in the rows — meaning if you multiply a single row by 3, the determinant gets multiplied by 3. Multiply all three rows by 3, and you multiply the determinant by 3 three times, i.e., 33=27.
Let’s walk through it step by step.
Recall the property for a single row scaling.
If B is the matrix obtained from A by multiplying one row by a scalar k, then ∣B∣=k∣A∣. This is a fundamental property of determinants.
Apply it to all rows.
3A means every entry of A is multiplied by 3. Equivalently, each of the three rows of A is multiplied by 3. So we can think of building 3A from A in three steps: multiply row 1 by 3, then row 2 by 3, then row 3 by 3.
Track the determinant after each step.
After scaling row 1: determinant becomes 3∣A∣.
Then scale row 2: determinant becomes 3⋅(3∣A∣)=32∣A∣. …
Method: Finding How a Scalar Multiplying a Whole Matrix Affects Its Determinant
Whenever a question asks for ∣kA∣ in terms of ∣A∣, remember that multiplying a matrix by a scalar multiplies every row by that scalar — and a determinant picks up one factor of k for each row it scales, not just one overall factor of k.
Steps
Step 1: Recall the single-row scaling property
If a matrix B is obtained from A by multiplying just one row by k, then ∣B∣=k∣A∣ — this is the multilinear-in-rows property of determinants, and it is the building block for everything else in this method.
Step 2: Recognise that kA scales every row, one at a time
kA multiplies all n rows of an n×n matrix A by k simultaneously. Mentally build kA from A by scaling row 1, then row 2, ..., then row n — applying Step 1's rule once per row.
Mistake 1: Writing ∣kA∣=k∣A∣, forgetting the exponent
Why it's wrong: this treats the determinant as if only one row (or the matrix as a single number) were being scaled, but kA scales every one of the n rows, so the determinant is multiplied by k a total of n times, giving kn, not k. This is only correct for a 1×1 matrix. Correct approach: always ask "how many rows does the scalar actually touch?" — for an n×n matrix, that answer is n, so the determinant scales by kn.
Mistake 2: Using the wrong order n when substituting into kn …
Same / Similar Concept — real previous-year questions on the same or a closely similar concept, not this exact question.
KCET 2021Set A-11 markMCQ
Q.If A and B are matrices of order 3 and ∣A∣=5, ∣B∣=3 then ∣3AB∣ is
(A) 425
(B) 405
(C) 565
(D) 585
›Reveal solutionSolution
Use the two determinant laws ∣kA∣=kn∣A∣ (order n) and ∣AB∣=∣A∣∣B∣.
Step 1 — The scalar-multiple law, and why the power n appears.
Multiplying a matrix by a scalar k multiplies every one of its n rows by k. A determinant is linear in each row separately, so each row contributes one factor of k:
The scalar triple product simplifies using linearity and the fact that any repeated vector makes the product zero. The final result is 3[a,b,c], which corresponds to option (D).
The scalar triple product [x,y,z] is defined as x⋅(y×z). It is linear in each argument, and it changes sign when two arguments are swapped. A key property: if any two vectors are the same (or linearly dependent), the triple product is zero. This problem is all about using these properties to expand a complicated-looking expression into simpler pieces.
We are given:
[a+2b−c,a−b,a−b−c]
Let’s denote the three vectors as:
u=a+2b−c,v=a−b,w=a−b−c
We need to compute [u,v,w].
Use linearity in the first argument.
The triple product is linear in each slot. So expand u:
[a+2b−c,v,w]=[a,v,w]+2[b,v,w]−[c,v,w]
Now expand each of these three terms using linearity in the second and third arguments.
Start with [a,v,w] where v=a−b and w=a−b−c:
[a,a−b,a−b−c]=[a,a,a−b−c]−[a,b,a−b−c]
The first term [a,a,…]=0 because two arguments are identical. So:
[a,v,w]=−[a,b,a−b−c]
Now expand the third argument:
−[a,b,a−b−c]=−[a,b,a]+[a,b,b]+[a,b,c]
The first two terms are zero (repeated vectors). So:
[a,v,w]=[a,b,c]
Next, compute [b,v,w].
[b,a−b,a−b−c]=[b,a,a−b−c]−[b,b,a−b−c]
The second term is zero. So:
[b,v,w]=[b,a,a−b−c]
Expand the third argument:
[b,a,a]−[b,a,b]−[b,a,c]
The first two terms are zero. So:
[b,v,w]=−[b,a,c]
Swapping two arguments changes sign: [b,a,c]=−[a,b,c]. Therefore: