There is also a geometrical interpretation to complex numbers and quaternions that I find enlightening, which is based on the algebra of multi-vectors. It is also related to the matrix representation of those quantities. If you define a vector basis, then you can define multi-vectors as the product of those basis creating directed area, volume, etc, in addition to directed length. The property of the vector multiplication is inherently anti-commutative, and is understood geometrically as changing the direction of the area, or volume.
For example, in 2-D, you may have the basis:
<br />
e_1, e_2<br />
Any 2-D vector can be represented by a linear combination:
<br />
X = a e_1 + b e_2<br />
The product of the basis gives the highest order multi-vector of the space, a bivector, which is anti-commutative.
<br />
B = e_1e_2 = -e_2e_1<br />
This has the property that the bi-vector times itself is -1, since a (unit) basis times itself is one.
<br />
B^2 = e_1e_2e_1e_2 = -e_2e_1e_1e_2 = -1<br />
Hmm, very similar to the imaginary unit. If you notice, you can take a normal 2D vector and multiply it by one of the basis, and create scalar and a bi-vector, which has the same algebra as complex numbers.
<br />
e_1X = a e_1e_1 + b e_1e_2 = a + bB<br />
All we have done is "prefer", or project out, the e_1 part. Equate e_1 to the "real" line and e_2 to the "imaginary" line.
The complex conjugate is just multiplying the vector from the other side:
<br />
Xe_1 = a e_1e_1 + b e_2e_1 = a - bB<br />
The quaternion is similar, but with three bi-vectors:
<br />
W = a + b e_2e_3 + c e_1e_3 + d e_1e_2<br />
where
<br />
i = e_2e_3, j = e_1e_3, k = e_1e_2<br />
EG
<br />
ij = e_2e_3e_1e_3 = - e_2e_3e_3e_1 = -e_2e_1 = e_1e_2 = k<br />
You can work out the rest to show it's equivalent.