As I understand, if we are to plot all possible values of $c\mathbf{v}$, we get a straight line, where it's $x$-coordinate spans from negative infinite to positive infinite, and same thing for its $y$-coordinate. I imagine if we are to draw the linear combinations of $\mathbf{v}_1$, $\mathbf{v}_2$, we would get a plane in $R^2$. But imaginations can fail.

@SalehenRahman What if $c_1=\alpha\cdot c_2$? ;-)

welcome back alizter

hi what

nothing

just saying hello

I was thinking about fractals

then I drew a doodle

now I need a program to write that doodle

:D

doodles are nice

@SalehenRahman Imagine that $c_1=\alpha\cdot c_2$. What is $span(c_1)$ ? $span(c_2)$ ?

@Hippalectryon are $c_1$ and $c_2$ vectors?

@MikeMiller @Alizter Noodles > Doodles

noodles are ok

@SalehenRahman I meant $v1,v2$

@MikeMiller What about fractal noodles ?

gross

@Hippalectryon Ah, now I see where you're going. Both spans represent the same line (I think that's the correct terminology).

Indeed @SalehenRahman

Indeed

$\mathbb{R}^2=span(v_1,v_2)$ iff they are linearly independant @SalehenRahman

@Hippalectryon thanks a lot! :)

:-)

Good night

This article on procedural planet generation is pretty interesting

More math-y than I expected it to be but I'm perfectly happy with it being so :)

@ZachSaucier Reminds of the the spherical-minecraft terrain generation algorithm

This might sound like a crazy question, but is it possible to extract a basis (or, if many, bases), for a span of vectors, regardless of whether they are linearly independent or not?

@SalehenRahman It is !

It's awfully easy from what you say :)

Won't the basis just be your vectors minus the ones that are linear combinations of others ?

@Hippalectryon Yeah. I just realized that after taking a quick glimpse at a YouTube video.

:-)

Can anybody tell me where the 1.28 comes from in problem two? mnstats.morris.umn.edu/introstat/stat2611/exam32001sol/…

@David I'd suggest you ask on main, at this hour not many people are in the chat

Thanks.

@David I don't know stats, but methinks it's the number of standard deviations away from the mean in which 80% falls.

How do I calculate that? So far in the class we've only used the standard normal distribution table, and -.8, .8, $\sqrt{.8}$... none of it comes to 1.28

certainly 1.28 is an approximation. I don't know how you go about approximating it either, though I can look that up.

@KarlKronenfeld, I just asked a question if you figure it out. Might as well earn some rep if you can.