Brainlet here

A 1-by-n matrix, where n is some positive integer.

direction and magnitude in 'space'

I thought that was the tip of a dick from the thumbnail.

unless you zoom in, it looks like a transparent dick
(the pic- not the vector)

See You were simply too late user. How many penises have you looked at today?

...

>actually lol'd ol

Dynamically allocated arrays.

I've played enough wing commander to recognize that engagement positioning.

Non-formally, a vector is basically a list of something. For example, (1, 0) is a vector and is a list of numbers. You can find similar definitions for each field of study out there.
Formally, a vector (in mathematics) is an element of a vector space, that is, an element of an algebraic structure that has 8 properties (Google "axioms of vector space").

Vector: a quantity with more than one element (more than one piece of information).

You can't measure everything using only numbers. Sometimes you need more than a number for a magnitude, for example, a force. It needs a number and direction. A quantity with more than one element.

A vector is like a number, with more numbers.

Polynomials and functions are vectors.

a quantity that is defined by a magnitude and an orientation

youtu.be/f5liqUk0ZTw?t=40s

If you zoom in on one it won't get pixelated.

A vector is a means of containing a direction and magnitude. Typically describes a linear combination of some basis. For a vector in 3d cartesian coordinates, (1, 2, 3) represents a vector whose direction can be drawn by taking an x, y, z plot and going +1 in x, +2 in y, and +3 in z. The length of the vector can then be found by taking sqrt(1^2 + 2^2 + 3^2).

Expressing a trajectory as a magnitude and direction For example, a plane flying at 500 mph north-northeast could be written as going along the vector (500, NNE) and is the exact same principal. However, that is done in polar coordinates rather than Cartesian.

Most of the math involved is just knowing how to get scalar quantities out of the vectors and being able to mathematically handle their interactions. So there are things like the dot and cross products.

If that's some spaceship game why not just fire your RCS thrusters and flip to point at the guy chasing you?

What the fuck are eigenvectors

>what are vectors?
A mathematical tool originally developed to analyze quantities that have direction in some space. Think force, velocity, acceleration, that kind of thing - it lets you manipulate stuff that has both direction and magnitude.

Later people figured out a bajillion other uses so a vector is anything with a direction and magnitude, or any matrix with a value for each dimension in some space if you're working with computers

youtu.be/PFDu9oVAE-g?t=3m

A vector is an element of a vector space.

A vector space is a collection of things in which there is some way to (((add))) these things together, and some other way to (((multiply))) these things by an ordinary number. When you do this the output must also be in your vector space.

Multiplication has to obey the distributive law as in a(v + u) is the same as av + au, and addition is commutative that is v + u = u + v.

The vector space needs to have a special element o such that o + v = v no matter what v you have.

You can define all of these addition and multiplication operations purely manually. It doesn't have to be length or whatever. So long as it obeys the laws I listed then it's fine.

That's it. There's no need for a vector to have "direction" or "magnitude" or anything. Those are examples of vector spaces, but not requirements.

a point that wants to go

>1-by-n matrix

you had one job

the axis u retard

...

>>>/reddit/

youtube.com/watch?v=bOIe0DIMbI8

>Nobel Prize Psychology
Actually he got an Ig Nobel.

"A vector is an arrow"
-- My first year linear algebra prof

>I fucking wish I was memeing

For the traditional n-dimensional vector space over the reals, linear transformations can be represented by matrices (A). These transform vectors (x,y) in a manner such that Ax = y, according to matrix multiplication.
An eigenvector of a linear transformation (a matrix) is a vector which when placed under the transformation is transformed to a vector parallel to the original vector, so that if x is an eigenvector of A, Ax = q*x, where q is a scalar. q is called the eigenvalue for the eigenvector x.
This can be extended to more abstract vector spaces be defining the eigenvector for a general linear transformation over that vector space. For example, on the vector space of infinitely-differential functions on the real numbers over the reals, the derivative is a linear transformation (e.g. d/dx (a*f(x)+b*g(x)) = a*f'(x)+b*g'(x)). The eigenfunctions (eigenvectors) of the derivative are those functions in which d/dx(f(x)) = q*f(x), which is the set of functions f(x) = C*exp(q*x) where C is a real number and q is the eigenvalue.

Has to also follow the laws of vector summation or it's not a true vector too