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JEE Mathematics 2025 Question with Solution

Let A=[aij]A = [a_{ij}] be a 2×22 \times 2 matrix such that aij{0,1}a_{ij} \in \{0, 1\} for all ii and jj. Let the random variable XX denote the possible values of the determinant of the matrix AA. Then, the variance of XX is:

  • A

    14\frac{1}{4}

  • B

    38\frac{3}{8}

  • C

    58\frac{5}{8}

  • D

    34\frac{3}{4}

Answer

Correct answer:B

Step-by-step solution

Standard Method

Given: A=[aij]A = [a_{ij}] is a 2×22 \times 2 matrix with each entry from {0,1}\{0,1\}.

Find: The variance of the random variable XX, where XX is the determinant of AA.

The determinant is

A=a11a22a12a21|A| = a_{11}a_{22} - a_{12}a_{21}

So the possible values of XX are 1,0,1-1, 0, 1.

From all possible matrices, the probability distribution is:

P(X=1)=316,P(X=0)=1016=58,P(X=1)=316P(X=-1)=\frac{3}{16}, \quad P(X=0)=\frac{10}{16}=\frac{5}{8}, \quad P(X=1)=\frac{3}{16}

Now,

Var(X)=E(X2)(E(X))2\text{Var}(X)=E(X^2)-\left(E(X)\right)^2

Also,

E(X)=(1)(316)+0(1016)+(1)(316)=0E(X)=(-1)\left(\frac{3}{16}\right)+0\left(\frac{10}{16}\right)+(1)\left(\frac{3}{16}\right)=0

And,

E(X2)=(1)2(316)+02(1016)+(1)2(316)=616=38E(X^2)=(-1)^2\left(\frac{3}{16}\right)+0^2\left(\frac{10}{16}\right)+(1)^2\left(\frac{3}{16}\right)=\frac{6}{16}=\frac{3}{8}

Therefore,

Var(X)=380=38\text{Var}(X)=\frac{3}{8}-0=\frac{3}{8}

Hence, the correct option is B.

Counting All Cases

Given: A=[abcd]A = \begin{bmatrix} a & b \\ c & d \end{bmatrix} where each of a,b,c,d{0,1}a,b,c,d \in \{0,1\}.

Find: The variance of X=det(A)X=\det(A).

Since each of the four entries can be chosen independently as 00 or 11, the total number of possible matrices is

22×2=162^{2 \times 2}=16

For a 2×22 \times 2 matrix,

det(A)=adbc\det(A)=ad-bc

Now adad and bcbc can each be either 00 or 11, so the possible values of adbcad-bc are

1,0,1-1, 0, 1

To get det(A)=1\det(A)=1, we need ad=1ad=1 and bc=0bc=0.

  • ad=1ad=1 happens only when a=1a=1 and d=1d=1, which is 11 way.
  • bc=0bc=0 happens in 33 ways: (b,c)=(0,0),(0,1),(1,0)(b,c)=(0,0),(0,1),(1,0). So,
P(X=1)=316P(X=1)=\frac{3}{16}

To get det(A)=1\det(A)=-1, we need ad=0ad=0 and bc=1bc=1.

  • bc=1bc=1 happens only when b=1b=1 and c=1c=1, which is 11 way.
  • ad=0ad=0 happens in 33 ways. So,
P(X=1)=316P(X=-1)=\frac{3}{16}

The remaining matrices have determinant 00:

16(3+3)=1016-(3+3)=10

Hence,

P(X=0)=1016=58P(X=0)=\frac{10}{16}=\frac{5}{8}

Now compute expectation:

E(X)=(1)(316)+0(1016)+1(316)=0E(X)=(-1)\left(\frac{3}{16}\right)+0\left(\frac{10}{16}\right)+1\left(\frac{3}{16}\right)=0

Next,

E(X2)=(1)2(316)+02(1016)+12(316)=616=38E(X^2)=(-1)^2\left(\frac{3}{16}\right)+0^2\left(\frac{10}{16}\right)+1^2\left(\frac{3}{16}\right)=\frac{6}{16}=\frac{3}{8}

Therefore,

Var(X)=E(X2)[E(X)]2=380=38\text{Var}(X)=E(X^2)-[E(X)]^2=\frac{3}{8}-0=\frac{3}{8}

Thus, the variance is 38\frac{3}{8} and the correct option is B.

Common mistakes

  • Assuming the determinant can take only the values 00 and 11. This is wrong because adbcad-bc can also be negative, giving 1-1. Always check all possible combinations of adad and bcbc.

  • Using incorrect probabilities for determinant values. The counts must come from all 1616 possible matrices, not from a partial listing. Count the cases for det(A)=1\det(A)=1 and det(A)=1\det(A)=-1 carefully, then assign the remaining cases to det(A)=0\det(A)=0.

  • Computing variance as only E(X2)E(X^2) without checking E(X)E(X). The formula is Var(X)=E(X2)[E(X)]2\text{Var}(X)=E(X^2)-[E(X)]^2. Here E(X)=0E(X)=0, but that must be shown, not assumed blindly.

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