Both Linearly Independent and Dependent?

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Is it possible for two vector functions of, for the moment's simplicity, one variable be both independent and dependent?

The reason I'm asking this is because on a problem from a book of mine (not homework), they put the following exercise:

Let $x^{(1)}(t)=\left (\begin{array}{cc} e^t \\ te^t\end{array} \right)$ and $x^{(2)}(t) = \left ( \begin{array}{cc} 1 \\ t \end{array} \right )$ . Show that $x^{(1)} (t)$ and $x^{(2)}(t)$ are linearly dependent at each point in the interval $0 ≤ t ≤ 1$. Nevertheless, show that $x^{(1)}(t)$ and $x^{(2)}(t)$ are linearly independent on $0≤t≤1$.

I would think that they're linearly dependent because $x^{(1)}(t)$ can simply be divided by the scalar $\frac{1}{e^t}$ (this is allowed because it is a never-zero exponential) to be equal to $x^{(2)}(t)$ $\forall t$, but because of the question I'm not too sure.

Could you give me some insight and/or guidance?

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Bad notation is bad....

Show that $x^{(1)}(t)$ and $x^{(2)}(t)$ are linearly dependent at each point in the interval $0 ≤ t ≤ 1$.

What you're being asked to prove here is that given $t\in [0,1]$, the vectors $x^{(1)}(t)$ and $x^{(2)}(t)$ are linearly dependent. There is nothing wrong with this.

Nevertheless, show that $x^{(1)}(t)$ and $x^{(2)}(t)$ are linearly independent on $0≤t≤1$.

What you're being asked to prove here, is that the vectors $x^{(1)}, x^{(2)}\colon [0,1]\to \mathbb R^{2\times 1}$ (vectors as in elements of a certain vector space - for example that of functions from $[0,1]$ to $\mathbb R^{2\times 1}$ - this vectors happen to be functions) are linearly independent.

That is, you're being asked to prove that $$\forall \alpha, \beta \in \mathbb R\left[\forall t\in [0,1]\left(\alpha x^{(1)}(t)+\beta x^{(2)}(t)=\begin{pmatrix}0\\0\end{pmatrix}\right)\implies \alpha =0=\beta\right].$$

Here the author is looking at $x^{(1)}(t)$ and $x^{(2)}(t)$ as if they were functions, which they are not. The notation is wrong. Correct would be:

Nevertheless, show that $x^{(1)}$ and $x^{(2)}$ are linearly independent on $0≤t≤1$.

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The question mixes two different vector spaces. You have two functions from $[0,1]\to\mathbb{R}^2$, $$ x^{(1)}\colon t\mapsto\begin{bmatrix}e^t\\te^t\end{bmatrix},\qquad x^{(2)}\colon t\mapsto\begin{bmatrix}1\\t\end{bmatrix} $$ These functions belong to the vector space $V$ of continuous maps from $[0,1]$ to $\mathbb{R}^2$ and form a linearly independent set in $V$. Indeed, if $$ \alpha x^{(1)}+\beta x^{(2)} $$ is the zero function, then it's easy to prove that $\alpha=\beta=0$ (just evaluate the functions at two suitable values of $t$). However, for each $t\in[0,1]$, you have $x^{(1)}(t)\in\mathbb{R}^2$ and $x^{(2)}(t)\in\mathbb{R}^2$; it can happen that, for some value of $t$ or even for all values of $t\in[0,1]$, these vectors form a linearly dependent set in the space $\mathbb{R}^2$.