What is the geometric interpretation of base?

susana

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I'm studying vectorial spaces at the moment.And I have felt some difficult to vizualise what is a base of a vectorial space.
For instant, how can I skecht a base in R2 or in R3?

Does anybody know of some material obout this issue? Or maybe does anybody can explain me?

Thanks
 
First, the word is "basis", not "base". If you are taking a course dealing with abstract vector spaces then you probably have, some time in the past, possibly in a physics course, drawn vectors as "directed line segments". That is, as a line segment (not "line"- a line segment has specific beginning and ending points while a line extends forever in both directions) with an "arrow head" drawn at one end.

Any two vectors in \(\displaystyle R^n\) and be basis vectors as long as one is not a multiple of the other. For example \(\displaystyle v_1= <1, 3>\) and \(\displaystyle v_2= <2, 4>\) are independent and so form a basis for \(\displaystyle R^2\). Take a sheet of paper and draw a Cartesian coordinate system on it. That is, draw two perpendicular lines crossing in the middle of the paper and label the origin, the point where the two lines intersect, (0, 0). Mark the two lines with coordinates, positive on one side of the origin, negative on the other. Most people make the axes horizontal and vertical, with positive on the right half of the horizontal line and on the top half of the vertical line, but that is not necessary. In any case, you now have a Cartesian coordinate system and so can label any point on the paper as "(x, y)". Mark the point (1, 3) and draw the line segment from (0, 0) to (1, 3) putting a little "arrow head" at (1, 3). That represents the vector <1, 3>. (Notice that I am using "<x, y>" for vectors and "(x, y)" for points in order to distinguish them. Do the same thing, marking the point (2, 4) in the coordinate system and draw the line segment from (0, 0) to (2, 4), putting a little "arrow head" at (2, 4).

Of course the whole point of a "basis" for a vector space is that any vector vector in the vector space can be written as a linear combination of the basis vectors. To show that here, geometrically, mark any point in the coordinate system, draw the line segment from (0, 0) to that point, draw a little "arrow head" at the point and label it "v". Extend the line segment representing \(\displaystyle v_1\) to a line extending infinitely in both directions. Draw a line parallel to \(\displaystyle v_2\) passing through the new point that formed v. Mark the point where they intersect (and they will precisely because the two basis vector are "independent") and draw a little "arrow head" on the line through \(\displaystyle v_1\) at that polnt and an arrow head on the line parallel to \(\displaystyle v_2\) at the point v. The first vector formed is a real number, \(\displaystyle a_1\) times \(\displaystyle v_1\), the second vector formed is a real number, \(\displaystyle a_2\) times \(\displaystyle v_2\) and the previous construction is their sum: \(\displaystyle v= a_1v_1+ a_2v_2\).

The same idea applies any basis for \(\displaystyle R^3\) with the added complication that a drawing on paper would be a two dimensional projection of a three dimensional situation on that paper. But you can at least visualize setting up a three dimensional xyz-coordinate system. Each given vector in \(\displaystyle R^3\) will be given as three numbers, <a, b, c>, which correspond to the point (a, b, c) in the coordinate system. Draw the line segment from (0, 0, 0) to (a, b, c) and draw a little "arrow head" at (a, b, c) to represent the vector <a, b, c>.

That's a very basic answer to your question, but then it is a very basic question!
 
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Vector Spaces are one of many algebraic structures (each with their own set of "algebra rules"), and are of particular importance. A basis is an example of what is called a minimal generating set. A generating set is one in which performing operations on the members of that set give you everything back. A minimal generating set is one of smallest size.
Example: <1,2>, <0,4>,<1,0> is a generating set for the vector space R^2.
Example: <0,4>,<1,0> is a generating set for the vector space R^2 of smallest size, so it is a basis.

Vector Spaces are among the nicest and easiest to study, simply because of the fact that they have the "invariant basis number" property. Essentially that this means, is that if you know everything about R^2, then you know everything about all two-dimensional vector spaces, for example: Polynomials of degree 1 or less or the complex numbers (as a vector space over R). Its really nice to know that all we need to care about is R^n when we want to discover something about a "weird" n-dimensional vector space.
 
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