Relationship between determinants and basis formation

In summary, the textbook statement that a column has to be parameterized when determinant is non-zero does not make sense to me because I know determinant is zero when a row of zeros in a matrix occur.
  • #1
neden
18
0
Hi,

I'm scratching my head over the statement from my textbook which states when determinant is non-zero, the set of vectors blah blah is a basis for r^3.

That does not make any sense to me because I know when a row of zeros in a matrix occur; the determinant is zero (through Gaussian Elimination), which means that a column has to be parameterized; then you are to set a arbitrary variables accordingly and from that one may create the needed basis.

What am I not understanding?
 
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  • #2
I'm afraid what you are saying makes no sense to me. I assume that the determinant you are talking about is the determinant of a matrix having the given vectors as columns. Second, I assume you are talking about a set of three given vectors in R3.

Yes, it is true a set of three vectors in R3 will form a basis for R3 if and only if the determinant of the matrix having those vectors as columns (or rows) is non-zero.

That is true because three vectors will be a basis for R3 if and only if they are independent: that the equation
[tex]x\begin{bmatrix}a \\ b\\ c\end{bmatrix}+ y\begin{bmatrix}d \\ e\\ f\end{bmatrix}+ z\begin{bmatrix}g \\ h \\ i\end{bmatrix}= \begin{bmatrix} 0 \\ 0 \\ 0\end{bmatrix}[/tex]
has only the "trivial" solution x= y= z= 0.

That is the same as saying that the three equations ax+ dy+ gz= 0, bx+ ey+ hz= 0, and cx+ fy+ iz= 0 have only the solution x= y= z= 0.

And that is true if and only if the "matrix of coefficients"
[tex]\begin{bmatrix}a & d & g \\ b & e & h \\ c & f & i\end{bmatrix}[/tex]
has non-zero determinant.

But I have no idea what you mean by "which means that a column has to be parameterized". What do you mean by "parameterizing" a column?
 
  • #3
Have a look at the http://www.math.oregonstate.edu/home/programs/undergrad/CalculusQuestStudyGuides/vcalc/lindep/lindep.html" . Three vectors u,v and w are tested for linear dependence.
The corresponding matrix has a row of zeroes (after row reduction). The parameter is then z and you can show that the vector w can be expressed as a linear combination of two other vectors u and v.
 
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FAQ: Relationship between determinants and basis formation

What are determinants and basis formation?

Determinants are mathematical values that are used to represent certain properties of a matrix. They are used to determine whether a matrix is invertible or singular. Basis formation is the process of creating a basis, which is a set of linearly independent vectors that can be used to represent all vectors in a given vector space.

What is the relationship between determinants and basis formation?

The relationship between determinants and basis formation lies in the fact that the determinant of a matrix is equal to the product of the basis vectors. This means that the determinant can be used to determine whether a set of vectors forms a basis by checking if the determinant is non-zero.

Why is understanding the relationship between determinants and basis formation important?

Understanding the relationship between determinants and basis formation is important because it allows us to determine if a set of vectors is linearly independent or not. It also helps us to determine if a matrix is invertible or not, which is crucial in many mathematical and scientific applications.

How are determinants and basis formation used in real-world applications?

Determinants and basis formation have a wide range of applications in fields such as physics, engineering, and economics. They are used to solve systems of linear equations, calculate areas and volumes, and determine the stability of a system. They are also used in computer graphics and data analysis.

What are some common misconceptions about the relationship between determinants and basis formation?

One common misconception is that the determinant is the same as the trace of a matrix. While the trace is the sum of the diagonal elements of a matrix, the determinant is a single value that represents the entire matrix. Another misconception is that the basis vectors must be orthogonal, when in fact they only need to be linearly independent.

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