Linear Dependence of Vectors: a, b, c

Yes, a= b= c= 0 so the vectors are linearly independent.In summary, the vectors a = [1 -1 0 1], b = [1 0 0 1], and c = [0 -1 0 1] are linearly independent, regardless of whether they are written as rows or columns in a matrix. This is determined by whether the only linear combination of the vectors that equals the zero vector has all coefficients equal to 0.
  • #1
theBEAST
364
0

Homework Statement


Are the vectors a = [1 -1 0 1], b = [1 0 0 1] and c =
[0 -1 0 1] linearly independent?


The Attempt at a Solution


I am mainly confused about whether or not I should have my matrix in row or column form to solve this:

r 1 -1 0 1
s 1 0 0 1
t 0 -1 0 1

or
r s t
1 1 0
-1 0 -1
0 0 0
1 1 1
 
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  • #2
The standard method is to write the matrix having the vectors as columns. However, that is only a convention. Doing it the other way should give the same result- the vectors will be independent, doing this the first way, if you do NOT get a row of all 0s. Doing it writing the vectors as rows, the vectors will be independent if you do NOT get a column of all 0s.

However, if you have trouble remembering this, it appears you are trying to memorize a method that is, to you, arbitrary. Personally, I prefer to use the definition of "linear independent" which you should have learned anyway. A set of vectors is "linearly independent" if and only if the only linear combination that is equal to the 0 vector has all coefficients equal to 0. That is, in this case, if a<1, -1, 0, 1>+ b<1, 0, 0, 1>+ c<0, -1, 0, 1>= <0, 0, 0, 0> then we must have a= b= c= 0. Is that true?

Of course, that gives <a+ b, -a- c, 0, a+ b+ c>= <0, 0, 0, 0> or the three equations a+ b= 0, -a-c= 0, a+b+ c= 0. From the first b= -a and from the second, c= -a. Put those into the third equation and solve for a.
 

1. What does it mean for vectors a, b, and c to be linearly dependent?

When vectors a, b, and c are linearly dependent, it means that one of the vectors can be expressed as a linear combination of the other two. In other words, one of the vectors can be written as a multiple of the other two vectors.

2. How can you determine if vectors a, b, and c are linearly dependent?

You can determine if vectors a, b, and c are linearly dependent by creating a matrix with the vectors as columns and performing row operations to reduce the matrix to row echelon form. If there is a row of zeros in the reduced matrix, then the vectors are linearly dependent.

3. What is the significance of linear dependence in vector spaces?

Linear dependence in vector spaces indicates that there is redundancy or overlap in the vectors. This can lead to inconsistencies or errors when using the vectors in mathematical operations, and can also limit the span or possible combinations of the vectors.

4. Can linear dependence occur in more than three vectors?

Yes, linear dependence can occur in any number of vectors. In fact, if there are n vectors in a vector space, then there can be at most n-1 linearly independent vectors.

5. How can linear dependence be used in practical applications?

Linear dependence can be used in various practical applications, such as data analysis and machine learning. For example, linear dependence can help identify and eliminate redundant variables in a dataset, making the analysis more efficient and accurate. It can also be used in linear regression models to determine the relationship between variables and make predictions.

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