Two nonzero vectors are linearly independent when implies . Their span then has dimension two. If they are linearly dependent, one is a scalar multiple of the other, so their span is a nonzero line and has dimension one. Thus the requested dimensions are two and one, respectively.
The dot product and corresponding Euclidean norm are
The Cauchy-Schwarz inequality states . If this is immediate. Otherwise the nonnegativity of a squared norm, with , gives
Multiplying by and taking square roots proves the inequality. Equality holds precisely when the vectors are linearly dependent. Expanding another squared norm and using the inequality gives
and hence the triangle inequality .
In , the two vectors lie in a common plane. If their directions make angle , the law of cosines gives . Comparing with the dot-product expansion yields
The sketch shows the same relation as a projection: multiply the length of by the signed component of in its direction. That component is negative for obtuse .
Figure 1.
Dot product as a signed projection in the plane of two vectors
. Details.
A unit vector is a vector of Euclidean norm one, equivalently . In particular the dot product of two unit vectors is the cosine of their mutual angle.
Put and . The linear independence assumption implies . Since is a unit vector, the Cauchy-Schwarz inequality gives
Equality holds exactly when points opposite to . Its required unit length then fixes the scale:
Here because both vectors have unit norm. The minimizing vector is unique, and the minimum pairwise dot-product sum of three unit vectors for these fixed is
The triangle inequality for the two unit vectors gives . Taking reciprocals and using the negative sign in yields
In fact equality would require , by the equality condition in the Cauchy-Schwarz inequality. Since the two vectors here are linearly independent, the inequality is strict for every admissible pair.
For the stated angle, , so . The minimizing unit vector is therefore , and
Indeed all three pairwise dot products equal , so the vectors lie in one plane, separated by degrees. This is also the global minimum pairwise dot-product sum of three unit vectors: for any three unit vectors,
so , with equality exactly when .

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