Please Critique My Solution Involving Linear Independence, Linear Dependence and Span

In summary: Since this is true for all $a,b,c$ satisfying (A2), we conclude that the statement in the problem is true.In summary, the statement "If $x$ and $y$ are linearly independent, and if $\{\textbf{x}, \textbf{y}, \textbf{z}\}$ is linearly dependent, then $\textbf{z}$ is in Span $\{\textbf{x},\textbf{y}\}$" is true. This can be proven by assuming that $x$ and $y$ are linearly independent and $z$ is linearly dependent, and then showing that $z$ must be in the span of $x$ and $y$. This is done
  • #1
bwpbruce
60
1
Problem:

True or False? If $x$ and $y$ are linearly independent, and if $\{\textbf{x}, \textbf{y}, \textbf{z}\}$ is linearly dependent, then $\textbf{z}$ is in Span $\{\textbf{x},\textbf{y}\}$

Solution:
$\textbf{True}$. If $a\textbf{x} + b\textbf{y} = \textbf{0}$ is true and if $a\textbf{x} + b\textbf{y} + c\textbf{z} = \textbf{0}$ is true, then $-a\textbf{x} -b\textbf{y} = \textbf{z}$ must also be true because when $c = 1$: \begin{align*}a\textbf{x} + b\textbf{y} + (1)\textbf{z} = \textbf{0}\end{align*}, we have the non-trivial solution. Furthermore,
\begin{align*}a\textbf{x} + b\textbf{y} + \textbf{z} = \textbf{0}\end{align*} becomes
\begin{align*}a\textbf{x} + b\textbf{y} = -\textbf{z}\end{align*} which simplifies to
\begin{align*}-a\textbf{x} + -b\textbf{y} = \textbf{z}\end{align*}
 
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  • #2
I'll use regular (not bold) letters from the end of the alphabet for vectors and letters from the beginning of the alphabet for numbers.

You may have shown that if $ax+by=0$ and $ax+by+cz=0$, then $z\in\operatorname{Span}\{x,y\}$. But the assumption in the problem was simply $ax+by+cz=0$ for some $a,b,c$; you were not authorized to assume that $ax+by=0$, especially with the same coefficients $a,b$. But you don't seem to actually use the assumption $ax+by=0$ later in the proof.

Further, what right do you have to assume that $c=1$? More precisely, of course, you can assume anything, but for the proof to be complete you also need to consider the case $c\ne 1$. Instead of assuming $c=1$ try dividing the equation by $c$. But first you need to prove that $c\ne0$.

A minor note is that to make a proof easy to read, it should start with assumptions, use them to deduce intermediate statements, use those to deduce other statements and progress in that way until you arrive at the conclusion. You, in contrast, started with assumptions and then announced a goal that you seem to have proved only at the end. In other words, if you are using words like "therefore", "so" and "thus", you are moving forward; but if you are using "because", then you reversed your direction and are now justifying facts announced ahead of time. It's a matter of style and readability, so this is not necessarily bad, but if you are learning to write proofs, the forward-moving style is preferable.
 
  • #3
Can you please provide me with an example of how to write a proof in the manner that you suggest. I'm awful with it and my proofs often ends up getting ripped to shreds in the same manner you just did.
 
  • #4
Assumptions:

(A1) $x,y$ are linearly independent, i.e., $ax+by=0$ implies $a=b=0$ for all $a,b$.

(A2) $x,y,z$ are linearly dependent, i.e., there exists $a,b,c$ such that $ax+by+cz=0$ and it is not the case that $a=b=c=0$.

Take some $a,b,c$ guaranteed to exist by (A2). Assume that $c=0$; then (A2) implies that $ax+by=0$, but it is not the case that $a=b=0$ (otherwise we would have $a=b=c=0$). But this contradicts (A1); therefore, the assumption $c=0$ was false and $c\ne0$. Dividing both sides of $ax+by+cz=0$ by $c$ we get $\frac{a}{c}x+\frac{b}{c}y+z=0$, or
\[
z=-\frac{a}{c}x-\frac{b}{c}y.
\]
Therefore, $z\in\operatorname{Span}\{x,y\}$.
 
  • #5
This solution is correct. However, it could be improved by providing more context and explanations for the steps taken. For example, it would be helpful to explain why $-a\textbf{x} -b\textbf{y} = \textbf{z}$ must be true and how this relates to the definition of linear dependence. Additionally, it would be beneficial to provide a visual representation or example to help clarify the solution. Overall, this solution effectively demonstrates an understanding of linear independence, linear dependence, and span, but could be improved by providing more thorough explanations and examples.
 

Related to Please Critique My Solution Involving Linear Independence, Linear Dependence and Span

1. What is the difference between linear independence and linear dependence?

Linear independence refers to a set of vectors in a vector space that cannot be written as a linear combination of each other. This means that none of the vectors can be expressed as a combination of the others. On the other hand, linear dependence refers to a set of vectors that can be expressed as a linear combination of each other. This means that one or more of the vectors can be written as a combination of the others.

2. How do you determine if a set of vectors is linearly independent or dependent?

To determine if a set of vectors is linearly independent, you can use the determinant method or the row reduction method. The determinant method involves creating a matrix with the vectors as its columns and calculating the determinant. If the determinant is non-zero, then the vectors are linearly independent. If the determinant is zero, then the vectors are linearly dependent. The row reduction method involves creating an augmented matrix with the vectors as its columns and reducing it to row-echelon form. If the resulting matrix has a row of all zeros, then the vectors are linearly dependent.

3. What is the span of a set of vectors?

The span of a set of vectors is the set of all possible linear combinations of those vectors. In other words, it is the set of all vectors that can be created by multiplying each vector by a scalar and adding them together.

4. How do you determine if a vector is in the span of a set of vectors?

To determine if a vector is in the span of a set of vectors, you can use the row reduction method. Create an augmented matrix with the given vector and the set of vectors as its columns and reduce it to row-echelon form. If the resulting matrix has a row of all zeros, then the given vector is in the span of the set of vectors. If the resulting matrix does not have a row of all zeros, then the given vector is not in the span of the set of vectors.

5. How can linear independence and linear dependence be applied in real-world problems?

Linear independence and linear dependence are important concepts in linear algebra and have many applications in various fields such as physics, engineering, and economics. For example, in physics, a set of linearly independent vectors can represent different forces acting on an object, and the span of these vectors can represent all the possible combinations of these forces. In engineering, linear dependence can indicate a redundant set of equations or a system with infinite solutions. In economics, linear independence can be used to determine the linear independence of a set of economic variables, which can help in decision-making processes.

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