Understanding Linear Algebra: Dependent vs. Independent Vectors Explained

In summary, linear independence and dependence refer to the relationship between vectors in linear algebra. A set of vectors is linearly independent if each vector adds a new dimension of direction, while a set of vectors is linearly dependent if some of the vectors can be described as a combination of the others. This concept is used in various scientific fields to describe the relationship between different variables.
  • #1
dervast
133
1
Hi i am new to linear algebra and i am not sure how i can translate some terms so i need some help with that
when we have vectorus u1,u2,.. un
and is k1*u1+k2*u2+...un*kn=0 then we say that these vectors are linear dependant or something like that
and if
k1*u1+k2*u2+...un*kn=0 and k1=0 and k2=0 and so on these vectores are linear independantly.
Do u know if my translation is correct?
 
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  • #2
Posted in the wrong place, but oh well.

We say [tex]u_1...u_n[/tex] are linearly independent if [tex]\sum{k_iu_i}=0[/tex] implies that all the k's are zero. They're linearly dependent if there are scalar k's such that not all of them are zero, and the above holds
 
  • #3
And what is the physical meaning of linearly dependence and independence? What do u understand when y hear someone saying that something is linearly independent or dependent?
 
  • #4
A set of vectors are linearly independent if, for n linearly independent vectors, you can describe n dimensions of space. So basically, it means that each vector you add describes a new dimension of direction. So the first vector points in a line, the second one lies in a plane with the first, the third lies in a volume with the first two, etc. If the vectors were linearly independent, then perhaps the first lies in a line, the second lies in a plane, and then the third also lies in that plane. So you don't get one dimension/vector
 
  • #5
Thx a lot for the answers.but have u ever heard of any scientist to be using linear independability in a different fashion that the one u have just described?
 

FAQ: Understanding Linear Algebra: Dependent vs. Independent Vectors Explained

What is the difference between dependent and independent vectors in linear algebra?

Linear algebra deals with the study of vector spaces and their properties. Dependent vectors are those that can be expressed as a linear combination of other vectors in the same vector space, while independent vectors are those that cannot be written as a linear combination of other vectors. This means that dependent vectors are redundant and do not add any new information to the vector space, while independent vectors are essential for defining the vector space.

How can I determine if a set of vectors is dependent or independent?

To determine if a set of vectors is dependent or independent, you can perform a simple test called the linear dependence test. This involves setting up a system of equations with the vectors as coefficients and solving for the variables. If the system has a non-trivial solution (i.e. not all variables equal to zero), then the vectors are dependent. If the only solution is when all variables are equal to zero, then the vectors are independent.

Can a set of dependent vectors be linearly combined to form a basis for a vector space?

No, a set of dependent vectors cannot form a basis for a vector space. A basis is a set of linearly independent vectors that span the entire vector space. Since dependent vectors are redundant and do not add any new information, they cannot form a basis. A basis must consist of independent vectors.

How does understanding dependent and independent vectors help in solving linear equations?

Understanding dependent and independent vectors is crucial in solving linear equations because it helps identify the number of solutions to the system of equations. If the vectors are independent, then the system has a unique solution. If the vectors are dependent, then the system has infinitely many solutions. This information can also be used to determine if a system of equations is consistent (has a solution) or inconsistent (has no solution).

Can dependent vectors be used to represent the same information as independent vectors?

Yes, dependent vectors can represent the same information as independent vectors, but they are not necessary. Independent vectors are the minimum number of vectors needed to define a vector space, and any additional vectors can be expressed as a linear combination of these independent vectors. Therefore, dependent vectors are not essential and can be removed without losing any information about the vector space.

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