Step 1: Concept
The Rank-Nullity Theorem states that for any linear transformation $T: V \to W$ where $V$ is finite-dimensional:
\[ \text{Rank}(T) + \text{Nullity}(T) = \dim(V) \]
Step 2: Key Formulas and Approach
Find the rank of matrix $A$ using row reduction, then use the Rank-Nullity Theorem to calculate nullity. Compare with Assertion A and Reason R.
Step 3: Step-by-step Explanation
• Evaluating Assertion A:
Given $A = \begin{bmatrix} 3 & 0 & -1
3 & 0 & -1
4 & 0 & 5 \end{bmatrix}$.
Apply $R_2 \to R_2 - R_1$:
\[ \begin{bmatrix} 3 & 0 & -1 0 & 0 & 0 4 & 0 & 5 \end{bmatrix} \]
The rows $[3, 0, -1]$ and $[4, 0, 5]$ are clearly linearly independent.
Therefore, the number of non-zero rows in row-echelon form is $2$, so $\text{Rank}(A) = 2$.
By Rank-Nullity theorem for $3 \times 3$ matrix ($n = 3$):
\[ \text{Nullity}(A) = 3 - \text{Rank}(A) = 3 - 2 = 1 \]
Hence, Assertion A is true.
• Evaluating Reason R:
Reason R states that $\text{Rank}(T) + \text{Nullity}(T) \neq n$.
By the fundamental Rank-Nullity Theorem, $\text{Rank}(T) + \text{Nullity}(T) = n$ strictly.
The claim that it is $\neq n$ contradicts the theorem.
Hence, Reason R is false.
Step 4: Final Answer
Assertion A is true, but Reason R is false. Thus, Option (C) is correct.