Understand the relationship between the dot product, length, and distance.
Understand the relationship between the dot product and orthogonality.
Vocabulary words:dot product, length, distance, unit vector, unit vector in the direction of .
Essential vocabulary word:orthogonal.
In this chapter, it will be necessary to find the closest point on a subspace to a given point, like so:
The closest point has the property that the difference between the two points is orthogonal, or perpendicular, to the subspace. For this reason, we need to develop notions of orthogonality, length, and distance.
Subsection6.1.1The Dot Product
The basic construction in this section is the dot product, which measures angles between vectors and computes the length of a vector.
The dot product of two vectors in is
Thinking of as column vectors, this is the same as
Notice that the dot product of two vectors is a scalar.
You can do arithmetic with dot products mostly as usual, as long as you remember you can only dot two vectors together, and that the result is a scalar.
Properties of the Dot Product
Let be vectors in and let be a scalar.
Distributivity with addition:
Distributivity with scalar multiplication:
The dot product of a vector with itself is an important special case:
Therefore, for any vector we have:
This leads to a good definition of length.
The length of a vector in is the number
It is easy to see why this is true for vectors in by the Pythagorean theorem.
For vectors in one can check that really is the length of although now this requires two applications of the Pythagorean theorem.
Note that the length of a vector is the length of the arrow; if we think in terms of points, then the length is its distance from the origin.