Example · High school

Terms

TermThis exampleWhy
spanning set ✓ The vectors $(1, 0)$, $(0, 1)$, and $(1, 1)$ form a spanning set of $\reals^2$, because every vector $(x, y)$ is $x (1, 0) + y (0, 1) + 0 (1, 1)$.
pairwise linearly independent ✓ The vectors $(1, 0)$, $(0, 1)$, and $(1, 1)$ are pairwise linearly independent, because no one of the three vectors is a scalar multiple of another.
basis ✗ The vectors $(1, 0)$, $(0, 1)$, and $(1, 1)$ are not a basis of $\reals^2$. They span $\reals^2$, but they are not independent: $(1, 1) = (1, 0) + (0, 1)$, so $(1, 1)$ is redundant.
linearly independent ✗ The vectors $(1, 0)$, $(0, 1)$, and $(1, 1)$ are not linearly independent, because $(1, 1) = (1, 0) + (0, 1)$.
orthogonal ✗ The vectors $(1, 0)$, $(0, 1)$, and $(1, 1)$ are not orthogonal, because the dot product of $(1, 0)$ and $(1, 1)$ is $1$.
orthonormal ✗ The vectors $(1, 0)$, $(0, 1)$, and $(1, 1)$ are not orthonormal, because the vectors are not orthogonal.

Distinctions using this example

  • Linearly independent vs. pairwise non-parallel: The vectors $(1, 0)$, $(0, 1)$, and $(1, 1)$ show that pairwise non-parallel vectors need not be linearly independent: no two of the vectors are parallel, but $(1, 1) = (1, 0) + (0, 1)$.

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