Is S Linearly Dependent in a Vector Space?

In summary, if a set of vectors S = {v1, v2, v3...vn} lies in a vector space, it is considered linearly dependent if one vector in S can be written as a linear combination of all the other vectors in S. This is determined by setting up a system of equations and solving for the coefficients. If the only solution is when all coefficients are 0, then the vectors are linearly independent. Otherwise, there are infinitely many solutions and the set of vectors is linearly dependent.
  • #1
newtomath
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If S= { v1, v2, v3...vn} lies in a vector space, S is linearly dependent if one vector in S is a linear combination of all the other vectors in S.


So I set up the below:

c1v1A + c2v2A +c3 v3A= 0
c1v1B + c2v2B +c3 v3B= 0
c1v1C + c2v2C +c3 v3C= 0

Since S lies in the vector space we know there are infinitely many solutions for (c1,c2,c3)

What am I missing here?
 
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  • #2
If the solution to your set of equations is c1 = c2 = c3 = 0, then the vectors v1, v2 and v3 are linearly independent. I'm not sure what exactly you're asking.
 
  • #3
I'm assuming that, for example, by v1A you mean the first component of the vector v1? Your setup is correct but such an equation like that is not guaranteed infinitely many solutions: there is either exactly one solution (in which case it must be c1 = c2 = c3 = 0) or infinitely many. If there is only the one trivial solution then the set of vectors is linearly independent.
 

1. What is linear dependency?

Linear dependency is a mathematical concept that describes the relationship between two or more variables. It means that one variable can be expressed as a linear combination of the other variables, or in simpler terms, one variable can be written as a multiple of another variable.

2. How do you prove linear dependency?

To prove linear dependency, you need to demonstrate that one variable can be written as a linear combination of the other variables. This can be done by setting up a system of equations and solving for the variables. If one variable can be expressed in terms of the others, then the variables are linearly dependent.

3. What is the purpose of proving linear dependency?

The purpose of proving linear dependency is to determine whether a set of variables can be reduced to a smaller set of independent variables. This can be useful in simplifying complex systems and finding relationships between variables.

4. What are the properties of linearly dependent variables?

Linearly dependent variables have a non-zero correlation, meaning that they are related to each other in some way. They also have a linear relationship, meaning that one can be expressed as a multiple of the other.

5. Can a set of linearly dependent variables be used in a statistical model?

Yes, a set of linearly dependent variables can be used in a statistical model. However, it is important to be cautious when using them as they can lead to issues such as multicollinearity, which can affect the accuracy of the model's predictions.

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