Finding the basis of the nullspace, can you see if i'm doing this right?

[mr_coffee]

Hello everyone, I think i did this right, but i want to make sure this is what they want. The questions says:
In each case find a basis for and caclulate the dimension of nullA:
Here is my work and problem!
http://img207.imageshack.us/img207/2948/lastscan6ib.jpg

I just found out its wrong...but why? the book got:
{[-2 4 1 0 0 ]^T, [7 -11 0 2 1]^T}
dim(nullA) = 2.
Those kind of resemble my columns, i got
[2 -4 0 0 0] and [-7 11 2 0 0], hm...

 

[HallsofIvy]

First of all, do you understand where the null space is?

If A: U->V is a linear transformation from U to V, then the null space of L is the subspace of U such that if x is in the null space, then Ax= 0.

Your A is a 5 by 3 matrix: from R⁵ to R³, but you give {[1,0,0], [0,1,0], [0,0,1]} as the basis for the null space. That's impossible! The nullspace of A a subpace of R⁵, not R³.

Those kind of resemble my columns, i got
[2 -4 0 0 0] and [-7 11 2 0 0], hm..."

Now, that's really mystiftying! In your image, your columns contain only 3 numbers, your rows, 5!

I haven't checked all of your arithmetic (you shift rows around in a way I find confusing) but assuming the last, row-reduced, matrix is correct, the equation AX= 0 becomes (letting X= [x, y, z, u, v]),
x+ 2z- 7v= 0, y- 4z+ 11v= 0, and u- 2v= 0. That is 3 equations in 5 unkowns so we can solve for 3 of them in terms of the other 2: in this row-reduced form, x= -2z+ 7v, y= 4z- 11v., u= 2v.
Taking z= 1, v= 0, that gives x= -2, y= 4, u= 0. One vector in the nullspace is [-2, 4, 1, 1, 0].
Taking z= 0, v= 1 gives x= 7, y= -11, u= 2. Another vector in the nullspace is [7, -11, 0, 2, 1].
Those 2 vectors constitute a basis for the nullspace.

The nullspace is 2 dimensional. That's no surprise. In order to "squeeze" a 5 dimensional space into a 3 dimensional space, at least 2 dimensions have to go to 0. Assuming no other dependencies, that would be exactly 2.

 

[mr_coffee]

ohh wow, i did totally screw that one up, thank you so much for the detailed explanation as always !