Q.If for three matrices π΄ = [πππ]πΓ4 , B = [πππ]πΓ3 πππ C = [πππ]πΓπ products π΄π΅ and π΄πΆ both are defined and are square matrices of same order, then value of π, π, π and π are:
(A) π = π = 3 πππ π = π = 4
(B) π = 2, π = 3 πππ π = π = 4
(C) π = π = 4 πππ π = π = 3
(D) π = 4, π = 2 πππ π = π = 3
πYou're viewing a preview β the full solution, concept, methods & PYQ mapping are locked.
π Start your 14-day free trial to unlock the full solution βConcept understanding β Matrix Multiplication Compatibility
Matrix Multiplication Compatibility: The Inner-Dimensions Rule
You cannot multiply just any two matrices. Multiplication is defined only when their sizes line up in a specific way, and this compatibility check is always the very first step of any product.
The Idea: A Row Meets a Column
When you multiply A by B, you take each row of A and pair it against each column of B, multiply corresponding entries, and add. For that pairing to work, a row of A must have exactly as many entries as a column of B.
Think of a handshake: each finger of one hand must meet a finger of the other. If one hand has 4 fingers and the other has 3, the handshake fails.
The Precise Statement
Let A be mΓn and B be pΓq.
AΓB is defined if and only if n=p β the number of columns of A equals the number of rows of B. The product C=AB then has order mΓq.
Writing the sizes side by side, (mΓn)(pΓq), the inner numbers (n,p) must match; the outer numbers (m,q) give the result's shape.
Why the Rule Exists
Each entry of the product is
cijβ=βk=1nβaikβbkjβ.
Here k runs over the columns of A (up to n) and the rows of B (up to p). If nξ =p, the sum runs out of matching terms and is meaningless β that is exactly why compatibility demands n=p.
Even when both AB and BA are defined, they usually differ. For A of order 2Γ3 and B of order 3Γ2, AB is 2Γ2 but BA is 3Γ3 β different sizes entirely. Matrix multiplication is not commutative.
Quick Check
| A | B | Defined? | Result | β¦
Apply the inner-dimension rule for products, then the square condition on the outer dimensions.
Step 1 β AB defined. A is mΓ4, B is nΓ3. Columns of A must equal rows of B: 4=n, so n=4.
Step 2 β AB square. AB has order mΓ3. Square means rows = columns: m=3.
Step 3 β AC defined. A is mΓ4, C is pΓq. Columns of A must equal rows of C: 4=p, so p=4. β¦
Compatibility forces n=4 and p=4; requiring both products to be square (and of the same order) forces m=3 and q=3. So m=q=3,Β n=p=4 β option (A).
The two rules we need
For a product XY to exist, the number of columns of X must equal the number of rows of Y, and the result takes the outer dimensions. A matrix is square when its number of rows equals its number of columns.
We are told A=[aijβ]mΓ4β, B=[bijβ]nΓ3β, C=[cijβ]pΓqβ, and that both AB and AC are defined square matrices of the same order.
Working the conditions
- AB is defined. Columns of A (which is 4) must equal rows of B (which is n):
4=nΒ βΒ n=4.
- AB is square. With AmΓ4β and B4Γ3β, the product AB has order mΓ3. For a square matrix the two must be equal:
m=3.
So AB is 3Γ3.
- AC is defined. Columns of A (4) must equal rows of C (p): 4=pΒ βΒ p=4. β¦
Method: Deducing unknown orders from "defined" and "square" conditions
Use this whenever a problem gives matrices with unknown orders and tells you certain products are defined and/or square, and asks you to pin down the unknowns.
Steps
Step 1: Turn each "product is defined" into an inner-dimension equation.
For a product XY to exist, the columns of X must equal the rows of Y. Write that equality for every product the problem says is defined.
XmΓnβYpΓqβΒ definedβΊn=p,resultΒ mΓq.
Step 2: Turn each "product is square" into an outer-dimension equation. β¦
Common Mistakes
Mistake 1: Assuming a square product must come from square factors.
Why it's wrong: order comes from the outer dimensions, so A3Γ4βB4Γ3β is a 3Γ3 (square) product even though neither factor is square. Correct approach: read "square" off the product's own order mΓq, not the factors.
Mistake 2: Matching outer dimensions for "defined". β¦
Showing the 12 most recent of 39 on this concept.
- CBSE 2025Set 65/1/11 markMCQQ.Let A=β10β3ββ242ββ1β11ββ, B=ββ2β5β7ββ, C=[9Β 8Β 7], which of the following is defined ? (A) Only AB (B) Only AC (C) Only BA (D) All AB, AC and BA
βΊReveal solutionSolution
Matrix multiplication is defined only when the number of columns in the first matrix equals the number of rows in the second. Here, A is 3Γ3, B is 3Γ1, and C is 1Γ3. So AB (3Γ3 times 3Γ1) is defined, AC (3Γ3 times 1Γ3) is defined, but BA (3Γ1 times 3Γ3) is not defined. The correct option is (B) Only AC.
The key idea is simple: you can multiply two matrices only if the inner dimensions match. That is, if the first matrix has size mΓn and the second has size pΓq, the product is defined iff n=p. The resulting matrix then has size mΓq.
Letβs check each product one by one.
1. Check AB
A is 3Γ3 (3 rows, 3 columns).
B is 3Γ1 (3 rows, 1 column).
The inner dimensions: 3 (columns of A) and 3 (rows of B) are equal. So AB is defined. The result will be a 3Γ1 matrix.
2. Check AC
A is 3Γ3.
C is 1Γ3 (1 row, 3 columns).
Inner dimensions: 3 (columns of A) and 1 (rows of C) β these are not equal. So AC is not defined. β¦
- CBSE 20241 markMCQQ.If for two non-zero square matrices A and B of the same order, (A+B)2=A2+B2, then : (A) AB=O (B) AB=βBA (C) BA=O (D) AB=BA Questions number 19 and 20 are Assertion and Reason based questions. Two statements are given, one labelled Assertion (A) and the other labelled Reason (R). Select the correct answer to these questions from the codes (A), (B), (C) and (D) as given below. (A) Both Assertion (A) and Reason (R) are true and Reason (R) is the correct explanation of Assertion (A). (B) Both Assertion (A) and Reason (R) are true, but Reason (R) is not the correct explanation of Assertion (A). (C) Assertion (A) is true, but Reason (R) is false. (D) Assertion (A) is false, but Reason (R) is true.
βΊReveal solutionSolution
The given equation (A+B)2=A2+B2 forces the cross terms to cancel, which means AB=βBA. The correct option is (B).
Why This Works: The Core Idea
Matrix multiplication is not commutative β AB is generally not equal to BA. When you expand (A+B)2, you get A2+AB+BA+B2. The given condition says this equals A2+B2, so the middle terms AB+BA must vanish. That gives AB=βBA, a condition called anti-commutativity.
Watch outA common mistake is to assume AB=O (zero matrix) from AB+BA=O. But thatβs only one possibility β the matrices could be non-zero and still satisfy AB=βBA. For example, take A=(00β10β) and B=(01β00β); then AB=(10β00β) and BA=(00β01β), so AB=βBA holds but neither product is zero.
Step-by-Step Reasoning
- Expand the square Since A and B are square matrices of the same order, we can multiply them. The distributive law holds for matrices, so:
(A+B)2=(A+B)(A+B)=A2+AB+BA+B2
- Apply the given condition The problem states:
(A+B)2=A2+B2
Substituting the expansion:
A2+AB+BA+B2=A2+B2
- Cancel the common terms Subtract A2+B2 from both sides:
AB+BA=O
where O is the zero matrix of the same order.
- Interpret the result The equation AB+BA=O is equivalent to:
AB=βBA
This is the definition of anti-commuting matrices. It does not force AB or BA to be zero individually β only that they are negatives of each other. β¦
- CBSE 2026Set 65/2/11 markMCQQ.If A and B are square matrices of same order, then which of the following statements is/are always true?(i) (A+B)(AβB)=A2βB2(ii) AB=BA(iii) (A+B)2=A2+AB+BA+B2(iv) AB=0βA=0 or B=0 (A) Only(i) and(iii) (B) Only(ii) and(iii) (C) Only(iii) (D) Only(iii) and (iv)
βΊReveal solutionSolution
Matrix multiplication is generally not commutative (ABξ =BA), which means many algebraic identities from scalar arithmetic do not hold for matrices. Only statement (iii) is always true, making (C) the correct option.
Concept and Intuition
When we work with numbers (scalars), we are used to properties like ab=ba (commutativity) and ab=0βa=0Β orΒ b=0. However, matrices behave differently. The most crucial distinction is that matrix multiplication is generally not commutative. This means that for two matrices A and B, AB is usually not equal to BA. This single property is the root cause for why many familiar algebraic identities, which rely on terms like AB and BA cancelling or combining, do not hold true for matrices.
Let's examine each statement with this fundamental understanding in mind.
Step-by-step Evaluation
- Evaluate statement (i): (A+B)(AβB)=A2βB2 To check if this is always true, we expand the left-hand side using the distributive property of matrix multiplication over addition, which does hold for matrices:
(A+B)(AβB)=A(AβB)+B(AβB)
=Aβ AβAβ B+Bβ AβBβ B
=A2βAB+BAβB2
For this expression to be equal to $A^2 - B^2$, we would need the terms $-AB + BA$ to be zero. This implies $BA = AB$. However, as discussed, matrix multiplication is generally not commutative, meaning $AB \neq BA$ in most cases. > [!WARNING] > This is a classic pitfall! The identity $(x+y)(x-y) = x^2 - y^2$ is true for scalars because $xy = yx$. For matrices, this is only true if $A$ and $B$ commute. Therefore, statement (i) is not always true.2. Evaluate statement (ii): AB=BA
This statement claims that matrix multiplication is always commutative. This is false. Matrix multiplication is generally not commutative. We can easily find counterexamples.
Consider:
A=(10β11β),B=(11β01β)
Then:AB=(10β11β)(11β01β)=(1β 1+1β 10β 1+1β 1β1β 0+1β 10β 0+1β 1β)=(21β11β)
And:BA=(11β01β)(10β11β)=(1β 1+0β 01β 1+1β 0β1β 1+0β 11β 1+1β 1β)=(11β12β)
Since $AB \neq BA$, statement (ii) is not always true.3. Evaluate statement (iii): (A+B)2=A2+AB+BA+B2
Let's expand the left-hand side:
(A+B)2=(A+B)(A+B)
Again, using the distributive property:=A(A+B)+B(A+B)
=Aβ A+Aβ B+Bβ A+Bβ B
$$= A^2 + AB + BA + B^2$$ β¦ - CBSE 2026Set A1 markMCQQ.If A=[1Β 2Β 3Β 4] and B=β1234ββ then AB=(a) [30](b) [10](c) [20](d) [40]
βΊReveal solutionSolution
A 1Γ4 row times a 4Γ1 column is the dot product =30.
β¦
- CBSE 2026Set ANNUAL1 markQ.If A=[1β4ββ22β35β] and B=β242β351ββ, then find AB.
βΊReveal solutionSolution
Multiply the 2Γ3 matrix A by the 3Γ2 matrix B row-by-column.
AB11β=1(2)+(β2)(4)+3(2)=2β8+6=0
AB12β=1(3)+(β2)(5)+3(1)=3β10+3=β4
AB21β=β4(2)+2(4)+5(2)=β8+8+10=10
AB22β=β4(3)+2(5)+5(1)=β12+10+5=3 β¦
- CBSE 2026Set ANNUAL1 markMCQQ.If A=[21β43β] then A2=(a) [49β161β](b) [26β122β](c) [169β1312β](d) None of these
βΊReveal solutionSolution
Multiply A by itself using row-by-column matrix multiplication; the result matches none of the printed options.
Given A=[21β43β].
A2=Aβ A=[21β43β][21β43β]
Entry (1,1): 2(2)+4(1)=4+4=8
Entry (1,2): 2(4)+4(3)=8+12=20
Entry (2,1): 1(2)+3(1)=2+3=5
Entry (2,2): 1(4)+3(3)=4+9=13
β¦
- CBSE 2026Set ANNUAL1 markQ.Find AB, if A=[00ββ12β] and B=[30β50β].
βΊReveal solutionSolution
Multiply the two 2Γ2 matrices row-by-column; every entry of the product turns out to be 0.
Given A=[00ββ12β] and B=[30β50β].
AB=[00ββ12β][30β50β]
Entry (1,1): 0(3)+(β1)(0)=0
Entry (1,2): 0(5)+(β1)(0)=0
Entry (2,1): 0(3)+2(0)=0
Entry (2,2): 0(5)+2(0)=0
β¦
- CBSE 2026Set ANNUAL1 markQ.If A=[1Β Β 2Β Β 5Β Β 7] and B=β6248ββ, write the orders of AB and BA.
βΊReveal solutionSolution
A1Γ4βB4Γ1ββ1Γ1; B4Γ1βA1Γ4ββ4Γ4.
A=[1Β 2Β 5Β 7] has order 1Γ4. B=β6248ββ has order 4Γ1.
- AB: (1Γ4)(4Γ1) β inner dimensions (4) agree, result order 1Γ1. β¦
- CBSE 2025Set E1 markMCQQ.[56ββ17β]β [23β14β]=(a) [733β1134β](b) [733β134β](c) [734β133β](d) [1639β525β]
βΊReveal solutionSolution
Row-by-column multiplication gives [733β134β].
Multiply [56ββ17β][23β14β] entry by entry:
- (1,1):5β 2+(β1)β 3=10β3=7
- (1,2):5β 1+(β1)β 4=5β4=1
- (2,1):6β 2+7β 3=12+21=33 β¦
- CBSE 2025Set E1 markMCQQ.[13β24β][10β01β]=(a) [10β04β](b) [13β24β](c) [10β24β](d) [13β20β]
βΊReveal solutionSolution
AI=A, so the product is the original matrix.
The second matrix [10β01β] is the 2Γ2 identity I. For any matrix A, AI=A. Hence β¦
- CBSE 2025Set E1 markMCQQ.[6β5β][β11β]=(a) [β6β5β](b) [β65β](c) [β1](d) [1]
βΊReveal solutionSolution
[6Β 5][β11β]=6(β1)+5(1)=β1, a 1Γ1 matrix.
A 1Γ2 matrix times a 2Γ1 matrix gives a 1Γ1 matrix: β¦
- CBSE 2025Set E1 markMCQQ.[13β24β][40β04β]=(a) [40β816β](b) [53β28β](c) [412β816β](d) [48β1216β]
βΊReveal solutionSolution
[40β04β]=4I, so the product is 4[13β24β].
Since [40β04β]=4I,
[13β24β](4I)=4[13β24β]=[412β816β]. β¦
πUnlock everything free for 14 days
- βFull step-by-step solutions
- βConcept-first explanations
- βMethods, shortcuts & mistakes
- βPYQ mapping + timed mock tests
Full access for 14 days. No credit card required.