Proof of Dot Product Vector Equation: u•v = ||u|| ||v|| cos (theta)

In summary, the Law of Cosines states that if u and v are nonzero vectors with an angle theta between them, then the dot product of u and v is equal to the product of the norms of u and v and the cosine of theta. This can also be derived by considering the triangle formed by u, v, and u-v and simplifying the dot product of u-v with itself.
  • #1
Justabeginner
309
1

Homework Statement


Prove that if u and v are nonzero vectors, and theta is the angle between them then u dot product v = ||u|| ||v|| cos (theta). Consider the triangle with sides u ,v , and u-v. The Law of Cosines implies that ||u-v||^2 = ||u||^2 + ||v||^2 - 2||u|| ||v|| cos(theta). On the other hand, ||u-v||^2 = (u-v) dot product (u-v)... Simplify this last expression, then equate the two formulas for ||u-v||^2.

Homework Equations


The Attempt at a Solution



I have no idea how to start! I thought of doing
cos(theta)= uxvx + uyvy / sqrt[(uxvy- vxuy)^2] + (uxvx + uyvy)^2] When x and y are subscripts, because
u= uxi + uyj
v= vxi + vyj
 
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  • #2
Expand the dot product ##(u-v) \cdot (u-v)## using distributivity.
 
  • #3
Yes I did that, and I get u^2 - 2uv + v^2.
But as for the left side ||u-v||^2, I get [sqrt(u^2 + v^2)]^2 = u^2 + v^2.
That isn't equal though.
 
  • #4
Justabeginner said:
Yes I did that, and I get u^2 - 2uv + v^2
Since u and v are vectors, you should write that as||u||2-2(u . v) + ||v||2. Now compare this with the law of cosines.
 
  • #5
So how is -2 ( u dot v) = -2 ||u|| ||v|| cos theta?
I don't understand. I thought once you take the norm of u and v you'll be left with -2 u times v cos theta?
 
  • #6
Justabeginner said:
So how is -2 ( u dot v) = -2 ||u|| ||v|| cos theta?
I don't understand. I thought once you take the norm of u and v you'll be left with -2 u times v cos theta?
The full expression before simplification is ##u \cdot u -2(u \cdot v) + v \cdot v##. The middle term is a projection, while the first and third terms are the norm of the vectors squared (which is also the projection of a vector onto itself)
 

FAQ: Proof of Dot Product Vector Equation: u•v = ||u|| ||v|| cos (theta)

What is the dot product vector equation?

The dot product vector equation is a mathematical formula used to calculate the scalar value of the product of two vectors. It is represented as u•v and is equal to the product of the magnitudes of the two vectors multiplied by the cosine of the angle between them.

How is the dot product vector equation derived?

The dot product vector equation is derived from the law of cosines. By using the cosine formula, we can find the angle between two vectors. This angle is then used in the equation to calculate the dot product of the two vectors.

What is the significance of the dot product vector equation?

The dot product vector equation is significant because it allows us to calculate the angle between two vectors and the magnitude of their product without having to use complex trigonometric functions. It also has many applications in physics, engineering, and computer graphics.

Can the dot product vector equation be used for any two vectors?

Yes, the dot product vector equation can be used for any two vectors in a three-dimensional space. However, for the equation to work, the vectors must be represented as column or row matrices.

How is the dot product vector equation related to the concept of orthogonality?

The dot product vector equation is closely related to the concept of orthogonality. Two vectors are said to be orthogonal if their dot product is equal to zero. This means that the angle between the two vectors is 90 degrees, and they are perpendicular to each other.

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