Step 1: Recall the correlation coefficient formula.
For any two variables \(i\) and \(j\), the correlation coefficient is \(\rho_{ij} = \dfrac{\text{Cov}(i,j)}{\sqrt{\text{Var}(i)\,\text{Var}(j)}}\), using the variances (diagonal entries) and covariance (off diagonal entry) from the matrix.
Step 2: Note that \(P\) has zero variance.
The entire row and column for \(P\) are zero, so \(\text{Var}(P) = 0\). This makes \(\rho_{PQ}\), \(\rho_{PR}\) and \(\rho_{PS}\) undefined (division by zero), so option (D), \(P\)-\(R\), cannot be a valid answer.
Step 3: Compute \(\rho_{QR}\).
\[ \rho_{QR} = \frac{1.85}{\sqrt{3.73 \times 0.93}} = \frac{1.85}{\sqrt{3.469}} = \frac{1.85}{1.863} \approx 0.99 \]
Step 4: Compute \(\rho_{QS}\).
\[ \rho_{QS} = \frac{3.23}{\sqrt{3.73 \times 2.79}} = \frac{3.23}{\sqrt{10.407}} = \frac{3.23}{3.226} \approx 1.00 \]
Step 5: Compute \(\rho_{RS}\).
\[ \rho_{RS} = \frac{1.61}{\sqrt{0.93 \times 2.79}} = \frac{1.61}{\sqrt{2.595}} = \frac{1.61}{1.611} \approx 1.00 \]
Step 6: Compare all three valid pairs.
All three pairs are strongly correlated, but from the given rounded covariance entries, the \(Q\)-\(S\) pair evaluates to the ratio closest to 1, so it is taken as showing the highest correlation. \[ \boxed{\text{Option (A), } Q\text{-}S} \]
Note: IIT Guwahati officially declared this question Marks-To-All (MTA) because it was found to be defective, since the \(Q\)-\(S\) and \(R\)-\(S\) correlations both round to essentially 1.00 from the given data, making the highest pair ambiguous, so every candidate was awarded marks for this question regardless of the option chosen.