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Do the following sets of vectors span \( \mathbb{R}^{3} \) ? Select an Answer 1. \[ \left[\begin{array}{c} 2 \\ -1 \\ -2 \end{array}\right],\left[\begin{array}{c} 2 \\ -1 \\ -3 \end{array}\right],\left[\begin{array}{l} 0 \\ 0 \\ 1 \end{array}\right] \] Select an Answer 2. \[ \left[\begin{array}{c} 1 \\ 2 \\ -1 \end{array}\right],\left[\begin{array}{c} 5 \\ -7 \\ 5 \end{array}\right],\left[\begin{array}{c} 6 \\ -3 \\ 3 \end{array}\right] \] Select an Answer 3. \[ \left[\begin{array}{c} -1 \\ 2 \\ 1 \end{array}\right],\left[\begin{array}{c} -4 \\ 8 \\ 3 \end{array}\right] \] Select an Answer 4. \[ \left[\begin{array}{c} -3 \\ 2 \\ 1 \end{array}\right],\left[\begin{array}{c} 6 \\ -4 \\ -3 \end{array}\right],\left[\begin{array}{c} 6 \\ -4 \\ -4 \end{array}\right],\left[\begin{array}{r} -21 \\ 14 \\ 11 \end{array}\right] \]

Ask by Ayala Pierce. in the United States
Feb 04,2025

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Answer

1. No 2. Yes 3. No 4. No

Solution

Let's analyze each set of vectors to determine whether they span \( \mathbb{R}^3 \). ### **1. Set 1** \[ \mathbf{v}_1 = \begin{bmatrix} 2 \\ -1 \\ -2 \end{bmatrix}, \quad \mathbf{v}_2 = \begin{bmatrix} 2 \\ -1 \\ -3 \end{bmatrix}, \quad \mathbf{v}_3 = \begin{bmatrix} 0 \\ 0 \\ 1 \end{bmatrix} \] **Analysis:** - Observe that \(\mathbf{v}_1 - \mathbf{v}_2 = \mathbf{v}_3\). - This means \(\mathbf{v}_3\) is a linear combination of \(\mathbf{v}_1\) and \(\mathbf{v}_2\), indicating that these vectors are linearly dependent. **Conclusion:** **They do not span \( \mathbb{R}^3 \).** --- ### **2. Set 2** \[ \mathbf{v}_1 = \begin{bmatrix} 1 \\ 2 \\ -1 \end{bmatrix}, \quad \mathbf{v}_2 = \begin{bmatrix} 5 \\ -7 \\ 5 \end{bmatrix}, \quad \mathbf{v}_3 = \begin{bmatrix} 6 \\ -3 \\ 3 \end{bmatrix} \] **Analysis:** - Compute the determinant of the matrix formed by these vectors: \[ \text{det} \begin{bmatrix} 1 & 5 & 6 \\ 2 & -7 & -3 \\ -1 & 5 & 3 \end{bmatrix} = -3 \neq 0 \] - A non-zero determinant indicates that the vectors are linearly independent. **Conclusion:** **They span \( \mathbb{R}^3 \).** --- ### **3. Set 3** \[ \mathbf{v}_1 = \begin{bmatrix} -1 \\ 2 \\ 1 \end{bmatrix}, \quad \mathbf{v}_2 = \begin{bmatrix} -4 \\ 8 \\ 3 \end{bmatrix} \] **Analysis:** - Only two vectors are provided in \( \mathbb{R}^3 \). - Even though these two vectors might be linearly independent, two vectors can at most span a 2-dimensional subspace in \( \mathbb{R}^3 \). **Conclusion:** **They do not span \( \mathbb{R}^3 \).** --- ### **4. Set 4** \[ \mathbf{v}_1 = \begin{bmatrix} -3 \\ 2 \\ 1 \end{bmatrix}, \quad \mathbf{v}_2 = \begin{bmatrix} 6 \\ -4 \\ -3 \end{bmatrix}, \quad \mathbf{v}_3 = \begin{bmatrix} 6 \\ -4 \\ -4 \end{bmatrix}, \quad \mathbf{v}_4 = \begin{bmatrix} -21 \\ 14 \\ 11 \end{bmatrix} \] **Analysis:** - Upon examination, all four vectors are linear combinations of \(\mathbf{v}_1\) and \(\mathbf{v}_2\). - For example: - \(\mathbf{v}_3 = 2\mathbf{v}_1 + 2\mathbf{v}_2\) - \(\mathbf{v}_4 = -1\mathbf{v}_1 - 4\mathbf{v}_2\) - This implies that all vectors lie within a 2-dimensional subspace of \( \mathbb{R}^3 \). **Conclusion:** **They do not span \( \mathbb{R}^3 \).** --- ### **Summary of Answers:** 1. **No** 2. **Yes** 3. **No** 4. **No**

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To determine if the given sets of vectors span \( \mathbb{R}^{3} \), we must check if they are linearly independent and if they form a basis for \(\mathbb{R}^{3\). 1. For the first set, we can write the vectors as: \[ \begin{pmatrix} 2 & 2 & 0 \\ -1 & -1 & 0 \\ -2 & -3 & 1 \end{pmatrix} \] The presence of the third vector allows us to fill the third dimension, so yes, this set spans \(\mathbb{R}^{3}\). 2. In the second set, note that the third vector can be expressed as a combination of the first two: \[ 6 \vec{v_1} - 3 \vec{v_2} \] which means they aren't independent, hence they do not span \(\mathbb{R}^{3}\). 3. The third set only has two vectors, meaning it cannot span a three-dimensional space like \(\mathbb{R}^{3}\). 4. In the final set, you can notice that one vector is a linear combination of the others, thus they will not span \(\mathbb{R}^{3}\). In conclusion: - The first set spans \(\mathbb{R}^{3}\). - The second, third, and fourth sets do not span \(\mathbb{R}^{3}\). Now for some extra knowledge! Vectors are like characters in a story—they need depth and variety to create a rich narrative! When you're trying to span \( \mathbb{R}^{3}\), think of it like painting a wall: you can't just use one color; you need a palette that includes multiple shades. Feeling a bit lost with the concept of linear independence? Imagine you’re at a party and want to bring friends from different groups! If all your friends know each other (same linear combination), you’ll end up wearing the same outfit as them (linearly dependent)! But if you grab diverse friends, you’re bringing unique flair to the gathering (linearly independent)!

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