Q.If A=1−202−1−10−21, find A−1. Using A−1, solve the system of linear equations x−2y=10, 2x−y−z=8, −2y+z=7.
🔒You're viewing a preview — the full solution, concept, methods & PYQ mapping are locked.
🔒 Start your 14-day free trial to unlock the full solution →Concept understanding — Inverse Matrix Method
The Inverse Matrix Method
Many problems reduce to a system of linear equations, for example
2x+3yx− y=8=−1.
The inverse matrix method solves such a system by writing it as a single matrix equation and then undoing the coefficient matrix with its inverse — the matrix analogue of dividing.
Writing the system as AX=B
Collect the coefficients, the unknowns and the constants:
A=(213−1),X=(xy),B=(8−1),
so the whole system becomes AX=B.
The idea
For numbers, ax=b gives x=a−1b provided a=0. The same works for matrices: if A is invertible, multiply AX=B on the left by A−1:
A−1(AX)=A−1B⇒IX=A−1B⇒X=A−1B.
X=A−1B
Multiplying on the left matters — matrix products do not commute, so BA−1 would be wrong.
When it works
The inverse A−1 exists only when detA=0, so:
- detA=0: the system is consistent with the unique solution X=A−1B.
- detA=0: no inverse; the system is either inconsistent (no solution) or has infinitely many — handle it by another method.
Worked steps
For the system above, detA=(2)(−1)−(3)(1)=−5=0, and
A−1=−51(−1−1−32).
Then …
Find A−1. For A=1−202−1−10−21, expanding along row 1 gives ∣A∣=1(−1−2)−2(−2−0)+0=−3+4=1. The cofactor matrix is −3−2−4212213, so
A−1=∣A∣1adjA=−322−211−423.
Relate the system to A. With all variables written out, x−2y+0z=10, 2x−y−z=8, 0x−2y+z=7, the coefficient matrix is
M=120−2−1−20−11=AT. …
A−1=−322−211−423. The system's coefficient matrix is AT, not A, so X=(A−1)TB, giving x=0, y=−5, z=−3.
Step 1 — Determinant of A
For A=1−202−1−10−21, expanding along the first row,
∣A∣=1(−1−2)−2(−2−0)+0=−3+4=1=0,
so A−1 exists.
Step 2 — Cofactors and adjoint
C11=−3, C12=2, C13=2,C21=−2, C22=1, C23=1,C31=−4, C32=2, C33=3.
The adjoint is the transpose of the cofactor matrix, and ∣A∣=1, so
A−1=adjA=−322−211−423.
Step 3 — Match the system to A
Write each equation with all three variables:
x−2y+0z=10,2x−y−z=8,0x−2y+z=7.
The coefficient matrix is
M=120−2−1−20−11=AT.
This is the key observation: the system is ATX=B, not AX=B. Reading off A−1 and multiplying by B directly would solve the wrong system.
Step 4 — Solve using (A−1)T …
Method: Solving a Linear System with the Inverse Matrix Method — Matching the Coefficient Matrix Carefully
Use this method whenever you're given a matrix A (and asked to find A−1), then a separate system of equations to solve "using" it — the key extra step beyond a routine inverse-matrix solve is confirming which matrix actually equals the system's coefficient matrix.
Steps
Step 1: Find A−1 using the adjoint
Compute ∣A∣, the cofactor matrix, and adj(A), then assemble A−1=∣A∣1adj(A). Do this once, before touching the system.
Step 2: Write the system with every variable shown explicitly
Rewrite each equation so every variable appears with an explicit coefficient, including any that are "missing" (write them with coefficient 0). This exposes the true coefficient matrix — skipping this step is the most common source of error in this question type.
Step 3: Compare the coefficient matrix against A …
Common Mistakes
Mistake 1: Assuming the given matrix A is automatically the system's coefficient matrix
Why it's wrong: writing the three equations in full (x−2y+0z=10, 2x−y−z=8, 0x−2y+z=7) gives a coefficient matrix that is actually AT, not A — the rows and columns of A have been swapped relative to the equations. Using X=A−1B directly here solves the wrong system entirely. Correct approach: always write out the coefficient matrix explicitly from the equations (filling in 0s for missing variables) and compare it to A before deciding whether to use A−1 or (A−1)T.
Mistake 2: Forgetting to include zero coefficients for missing variables …
- COMEDK 2025Set 2025-M1 markMCQQ.If A=0−1210−3−230 then A−1 (A) equal to −121(adjA) (B) equal to −12 (C) equal to 121(adjA) (D) doesn't exit
›Reveal solutionSolution
The matrix is skew-symmetric of odd order, so its determinant is zero and the inverse does not exist. The correct option is (D).
We are given
A=0−1210−3−230.
Notice that AT=−A; that is, A is skew-symmetric. For any skew-symmetric matrix of odd order, the determinant is always zero. Here the order is 3 (odd), so detA=0. A matrix with zero determinant is singular and has no inverse.
Let’s verify quickly:
- Compute the determinant directly:
detA=0⋅(0⋅0−3⋅(−3))−1⋅((−1)⋅0−3⋅2)+(−2)⋅((−1)⋅(−3)−0⋅2)
=0−1⋅(0−6)+(−2)⋅(3−0)=−1⋅(−6)+(−2)⋅3=6−6=0.
-
Since detA=0, A is singular, so A−1 does not exist.
-
Among the options:
- (A) and (C) involve adjA scaled by a nonzero constant — but the inverse doesn’t exist, so these are meaningless. …
- COMEDK 2023Set 2023-M1 markMCQQ.If A=[2324], then A−1 equals to (A) [2−3/21−1] (B) [2−3/2−11] (C) [−23/21−1] (D) [−23/2−11]
›Reveal solutionSolution
A−1=detA1adj A with detA=2 gives [2−3/2−11].
A=[2324], detA=2⋅4−2⋅3=8−6=2.
For a 2×2 matrix, adj A=[4−3−22].
A−1=21[4−3−22]=[2−3/2−11]. …
- COMEDK 2024Set 2024-M1 markMCQQ.If A=−113121231 then the inverse of (AI)t (where I is an identity matrix) is (A) 1−11−87−55−43 (B) −18−51−74−15−3 (C) 1−10875−5−43 (D) 1−85−17−41−53
›Reveal solutionSolution
The problem asks for the inverse of (AI)t, which is actually the transpose of A itself (since AI=A). We compute A−1 and then transpose it; the result matches option (D).
We are given
A=−113121231
and asked for the inverse of (AI)t.
Concept and intuition:
First, note that AI=A (multiplying by the identity does nothing). So (AI)t=At. The problem is really asking for (At)−1. A key property: the inverse of a transpose is the transpose of the inverse, i.e. (At)−1=(A−1)t. So we can find A−1 and then transpose it. This is often easier than inverting At directly.
Let’s proceed step by step.
- Find the determinant of A to ensure it’s invertible.
det(A)=(−1)2131−11331+21321
Compute each:
- 2131=2⋅1−3⋅1=−1
- 1331=1⋅1−3⋅3=1−9=−8
- 1321=1⋅1−2⋅3=1−6=−5
So
det(A)=(−1)(−1)−1(−8)+2(−5)=1+8−10=−1
Since det(A)=−1=0, A is invertible.
-
Find the matrix of cofactors for A.
For each entry aij, the cofactor is Cij=(−1)i+jMij, where Mij is the minor (determinant of the matrix after removing row i and column j).
-
Row 1:
C11=+2131=−1
C12=−1331=−(−8)=8
C13=+1321=−5
-
Row 2:
C21=−1121=−(1⋅1−2⋅1)=−(1−2)=1
C22=+−1321=(−1⋅1−2⋅3)=−1−6=−7
C23=−−1311=−((−1)⋅1−1⋅3)=−(−1−3)=4
-
Row 3:
C31=+1223=1⋅3−2⋅2=3−4=−1
C32=−−1123=−((−1)⋅3−2⋅1)=−(−3−2)=5
C33=+−1112=(−1)⋅2−1⋅1=−2−1=−3
So the cofactor matrix is
-
- COMEDK 2023Set 2023-E1 markMCQQ.Solution of x−y+z=4;x−2y+2z=9 and 2x+y+3z=1 is (A) x=3;y=6;z=9 (B) x=−4;y=−3;z=2 (C) x=−1;y=−3;z=2 (D) x=2;y=4;z=6
›Reveal solutionSolution
Verification: (1) -1 + 3 + 2 = 4 OK; (2) -1 + 6 + 4 = 9 OK; (3) -2 - 3 + 6 = 1 OK.
Concept: solving a 3x3 linear system (here fastest by elimination, then verified by substitution).
x - y + z = 4 ... (1)
x - 2y + 2z = 9 ... (2)
2x + y + 3z = 1 ... (3)
(2) - (1): -y + z = 5 => z = y + 5.
(3) - 2*(1): (2x + y + 3z) - (2x - 2y + 2z) = 1 - 8 => 3y + z = -7.
Substitute z = y + 5: 3y + y + 5 = -7 => 4y = -12 => y = -3, hence z = 2. …
- COMEDK 2026Set 2026-A1 markMCQQ.Let A be a square matrix of order 3×3. If ∣A∣=−4, then the value of −2A−1 is: (A) −1 (B) 2 (C) 321 (D) −161
›Reveal solutionSolution
The determinant of a scalar multiple of an inverse matrix is found by factoring out the scalar raised to the matrix order, then using the property that ∣A−1∣=1/∣A∣. The result is 321, so the correct option is (C).
Concept & Intuition
We are asked for −2A−1, which means the determinant of the matrix A−1 multiplied by the scalar −21. Two key facts do all the work:
- For any n×n matrix M and scalar c, ∣cM∣=cn∣M∣.
- ∣A−1∣=1/∣A∣ (since AA−1=I and ∣A∣∣A−1∣=1).
So we just combine these: factor out the scalar, then replace ∣A−1∣ with 1/∣A∣, and plug in ∣A∣=−4.
Step-by-step
-
Interpret the expression
−2A−1 means −21⋅A−1. So we want ∣(−21)A−1∣.
-
Factor out the scalar
For a 3×3 matrix, ∣cM∣=c3∣M∣. Here c=−21, so
−21A−1=(−21)3⋅∣A−1∣=−81⋅∣A−1∣.
- Use the inverse determinant property Since ∣A−1∣=∣A∣1 and ∣A∣=−4, we have ∣A−1∣=−41=−41.…
- COMEDK 2025Set 2025-A1 markMCQQ.The cost of 4 kg onion, 3 kg wheat and 2 kg rice is ₹ 500 . The cost of 1 kg onion, 2 kg wheat and 3 kg rice is ₹ 300 . The cost of 6 kg onion, 2 kg wheat and 3 kg rice is ₹ 575 . The above situation can be represented in matrix form as AX=B. Then 5A−1= (A) 5 (B) 125 (C) 1 (D) 25
›Reveal solutionSolution
The problem gives three linear equations in three unknowns (prices per kg). Writing them as AX=B, we need 5A−1. Since 5A−1=53⋅∣A−1∣=125/∣A∣, we compute ∣A∣ from the coefficients and find it equals 125, so the answer is 1.
We have three commodities: onion (let’s call the price per kg x), wheat (y), and rice (z). The given costs translate to:
- 4x+3y+2z=500
- 1x+2y+3z=300
- 6x+2y+3z=575
The matrix form AX=B means A is the 3×3 coefficient matrix, X=[x,y,z]T, and B=[500,300,575]T.
We are asked for 5A−1. The key idea: for any square matrix A, kA−1=kn⋅∣A−1∣, where n is the order (here n=3). And ∣A−1∣=1/∣A∣. So the problem reduces to finding ∣A∣.
Step-by-step solution:
- Write the coefficient matrix A From the equations:
A=416322233
- Compute the determinant ∣A∣ Expand along the first row:
∣A∣=4⋅2233−3⋅1633+2⋅1622
- First minor: (2)(3)−(3)(2)=6−6=0
- Second minor: (1)(3)−(3)(6)=3−18=−15
- Third minor: (1)(2)−(2)(6)=2−12=−10
So:
∣A∣=4(0)−3(−15)+2(−10)=0+45−20=25 …
- KCET 2018Set A-11 markMCQQ.If [1−111][xy]=[24], then the values of x and y respectively are (A) −3,−1 (B) 1,3 (C) 3,1 (D) −1,3
›Reveal solutionSolution
This is a 2×2 matrix equation that can be solved by multiplying both sides by the inverse of the coefficient matrix. The values are x=−1 and y=3, which corresponds to option (D).
The core idea here is that a matrix equation of the form Av=b is solved exactly like the scalar equation ax=b — you multiply both sides by the inverse of A (provided it exists). The only difference is that "division" becomes multiplication by A−1, and order matters because matrix multiplication is not commutative.
Let the coefficient matrix be A=[1−111], the unknown vector be v=[xy], and the constant vector be b=[24]. So we have Av=b.
-
Check if A is invertible.
Compute the determinant:
det(A)=(1)(1)−(1)(−1)=1+1=2.
Since det(A)=0, the inverse exists.
-
Find A−1.
For a 2×2 matrix [acbd], the inverse is det(A)1[d−c−ba].
So here:
A−1=21[11−11].
-
Multiply both sides by A−1 on the left.
Since A−1A=I, we get:
v=A−1b.
Compute:
[xy]=21[11−11][24].
-
Perform the multiplication.
First row: 1⋅2+(−1)⋅4=2−4=−2.
Second row: 1⋅2+1⋅4=2+4=6. …
-
- COMEDK 2025Set 2025-E1 markMCQQ.If A=401λ21−353 then A−1 exists if : (A) λ=2 (B) λ=0 (C) λ=2 (D) λ=−2
›Reveal solutionSolution
A−1 exists ⟺detA=0. Here detA=5λ+10, so we need λ=−2.
For A−1 to exist, A must be non-singular: detA=0.
A=401λ21−353
Expand along the first row:
detA=4(2⋅3−5⋅1)−λ(0⋅3−5⋅1)+(−3)(0⋅1−2⋅1) …
- KCET 2024Set A-11 markMCQQ.If P=112α34334 is the adjoint of a 3×3 matrix A and ∣A∣=4, then α is equal to (A) 4 (B) 5 (C) 11 (D) 0
›Reveal solutionSolution
The key idea is that for a 3×3 matrix A, ∣adj(A)∣=∣A∣2. We are given P=adj(A) and ∣A∣=4, so ∣P∣=42=16. Computing the determinant of P and setting it equal to 16 gives α=11.
-
The core relationship. For any square matrix A, the product A⋅adj(A)=∣A∣I. Taking determinants of both sides gives ∣A∣⋅∣adj(A)∣=∣A∣n, where n is the order of the matrix. For a 3×3 matrix (n=3), this simplifies to ∣adj(A)∣=∣A∣2.
-
Apply it to the given data. We are told P=adj(A) and ∣A∣=4. Therefore, the determinant of P must be ∣P∣=∣adj(A)∣=∣A∣2=42=16.
-
Compute the determinant of P. We have P=112α34334. Let's expand along the first row:
∣P∣=1⋅(3⋅4−3⋅4)−α⋅(1⋅4−3⋅2)+3⋅(1⋅4−3⋅2)
$$|P| = 1 \cdot (12 - 12) - \alpha \cdot (4 - 6) + 3 \cdot (4 - 6)$$ … -
- KCET 2019Set A-11 markMCQQ.If A=[1432], B=[21−12], then ∣ABB′∣= (A) 50 (B) −250 (C) 100 (D) 250
›Reveal solutionSolution
Use ∣XY∣=∣X∣∣Y∣ and ∣B′∣=∣B∣, so the answer is just ∣A∣⋅∣B∣2 — no matrix multiplication is needed.
Step 1 — The property that makes this a one-liner.
For square matrices of the same order, the determinant is multiplicative:
∣XY∣=∣X∣∣Y∣.
Also, transposing a matrix never changes its determinant: ∣B′∣=∣B∣. Therefore
∣ABB′∣=∣A∣∣B∣∣B′∣=∣A∣∣B∣2.
Actually multiplying the three 2×2 matrices out would work too, but it is far more error-prone.
Step 2 — Compute ∣A∣.
A=[1432] ⇒ ∣A∣=(1)(2)−(3)(4)=2−12=−10.
Step 3 — Compute ∣B∣. …
- KCET 2021Set A-11 markMCQQ.Let M be 2×2 symmetric matrix with integer entries, then M is invertible if (A) the first column of M is the transpose of second row of M (B) the second row of M is the transpose of first column of M (C) M is a diagonal matrix with non-zero entries in the principal diagonal (D) The product of entries in the principal diagonal of M is the product of entries in the other diagonal.
›Reveal solutionSolution
For a 2×2 symmetric integer matrix, invertibility depends on the determinant being non-zero. Only option (C) guarantees this.
The Concept: Invertibility and the Determinant
For any square matrix, invertibility is equivalent to having a non-zero determinant. For a 2×2 matrix M=(acbd), the determinant is det(M)=ad−bc. The matrix is invertible if and only if ad−bc=0.
The problem adds two constraints: M is symmetric (b=c) and all entries are integers. So M=(abbd) with a,b,d∈Z, and det(M)=ad−b2.
We need to check which condition guarantees that ad−b2=0.
Step-by-Step Analysis
1. Understanding the conditions in (A) and (B)
Let M=(acbd). Since M is symmetric, b=c.
-
Condition (A): "the first column of M is the transpose of the second row of M"
- First column: (ab)
- Second row: (bd), its transpose is (bd)
- Equality gives: (ab)=(bd), so a=b and b=d, hence a=b=d.
- Then M=(aaaa), determinant =a⋅a−a⋅a=0. So M is not invertible.
-
Condition (B): "the second row of M is the transpose of the first column of M"
- Second row: (bd)
- Transpose of first column: (ab)
- Equality gives: (bd)=(ab), so b=a and d=b, hence a=b=d again.
- Same matrix, determinant =0. Not invertible.
Watch outConditions (A) and (B) look different but both force all entries to be equal, making the determinant zero. A common mistake is to think they describe different matrices — they don't, for a symmetric 2×2 matrix.
2. Checking condition (C) …
-
🎓Unlock everything free for 14 days
- ✓Full step-by-step solutions
- ✓Concept-first explanations
- ✓Methods, shortcuts & mistakes
- ✓PYQ mapping + timed mock tests
Full access for 14 days. No credit card required.