Question
When the determinant of an
matrix is zero, we know
At least one row is a linear combination of the others.
Any linear combination of the
rows sums to zero.
Exactly one row is a linear combination of the others.
Every row is a linear combination of the others.
Each row after the first one is a linear combination of the rows above it.
At least one row is a linear combination of the others.
Any linear combination of the
Exactly one row is a linear combination of the others.
Every row is a linear combination of the others.
Each row after the first one is a linear combination of the rows above it.
Ask by Wood Collins. in the United States
Mar 23,2025
Upstudy AI Solution
Tutor-Verified Answer
Answer
At least one row is a linear combination of the others.
Solution
We are given an
matrix with zero determinant. The key property of such a matrix is that its rows (or columns) are linearly dependent. This means there exists a set of scalars (not all zero) such that a linear combination of the rows is zero.
Let’s examine each statement:
-
At least one row is a linear combination of the others.
Since the rows are linearly dependent, there exists at least one row that can be expressed as a linear combination of the other rows. This statement is true. -
Any linear combination of the
rows sums to zero.
In general, any linear combination of the rows does not necessarily equal the zero row unless the coefficients are chosen in a specific way to yield the dependency relation. This statement is false. -
Exactly one row is a linear combination of the others.
There is no restriction that only one row must be a combination of the others; in some cases, more than one row could be redundant. This statement is false. -
Every row is a linear combination of the others.
It is not required that every row be expressible as a linear combination of the others; linear dependence only guarantees the existence of at least one such row. This statement is false. -
Each row after the first one is a linear combination of the rows above it.
This is a specific structure (like what happens in row echelon form when there is a complete dependency) and is not guaranteed by the condition of having a zero determinant in general. This statement is false.
Thus, the only correct statement is the first one:
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Mind Expander
When the determinant of an
matrix is zero, it indicates that the rows (or columns) of the matrix are linearly dependent. This means you can find at least one row that can be expressed as a combination of the others, leading to the intuition that the matrix does not have full rank and, therefore, does not span the entire
-dimensional space.
In practical applications, this situation often arises in systems of linear equations. If you encounter a determinant of zero, it’s a signal that some equations might be redundant or that the system may have either no solution or infinitely many solutions, making it essential to analyze the system further to determine the nature of its solutions.