Urgent: Linear Algebra Question(Please verify)

In summary, the given vectors can be written as linear combinations of each other, showing that the spans of the two sets are equal. This can be proven by finding the values of x_1 and x_2 that make the original equation true and showing that these values can be used to express vectors in one span as linear combinations of vectors in the other span.
  • #1
Mathman23
254
0
(a)

show that the vector (2,7,6) be we written as a linear combination of the vectors

(1,3,2) and (0,1,2)

(b) show that the vector (-1,0,4) can be written as a linear combination of the vectors (1,3,2) and (0,1,2)

(c)

show that Span((1,3,2),(0,1,2)) = Span( (2,7,6), (-1,0,4))

My solution (a).

I write vectors in equation form

[tex]x_1 \[ \[ \begin{array}{c} 1 \\ 3 \\ 2 \end{array} \] + x_2 \[ \begin{array}{dd} 0 \\ 1 \\ 2 \end{array} \] =
\[ \begin{array}{c} 2 \\ 7 \\ 6 \end{array} \] [/tex]

which can be rewritten to

[tex] \[ \begin{array}{ccc} x_{1} \\ 3x_{1} + x_{2} \\ 2x_{1} + 2x_{2} \end{array} \] = \[ \begin{array}{c} 2 \\ 7 \\ 6 \end{array} \][/tex]

There must exist x_1 and x_2 which makes the above set of equations true.

These are found be rewritten the system into its equivalent coefficient matrix.

[tex] \[ \begin{array}{ccc} 1 & 0 & 2 \\ 3 & 1 & 7 \\ 2 & 2 & 6 \end{array} \] [/tex]

using row reduction I get

[tex] \[ \begin{array}{ccc} 1 & 0 & 2 \\ 0 & 1 & 1 \\ 0 & 0 & 0 \end{array} \] \mathrm[/tex]


which gives x_1 = 2 and x_2 = 1

If I insert into the original equation, then values of x_1 and x_2 make it true.

(b)

Following the same method used in (a) I get x1 = -1 and x_2 = 3.

(c)

How do I use these results to prove that Span((1,3,2),(0,1,2)) = Span((2,7,6),(-1,0,4)) ?

Can I claim the set of vectors are dependent, and therefore their spans equal each other?

Best Regards
Fred
 
Last edited:
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  • #2
The span of a set of vectors is the set of all (finite) linear combinations of vectors in the set. So a vector is in span((1,3,2),(0,1,2)) iff it is of the form a(1,3,2)+b(0,1,2) for some real numbers a and b, and similarly for span((2,7,6),(-1,0,4)), with vectors in this space having the form c(2,7,6)+d(-1,0,4). See if you can always get a pair (c,d) from (a,b) and vice versa.
 

1. What is Linear Algebra?

Linear Algebra is a branch of mathematics that deals with the study of linear equations and their representations through matrices and vectors. It involves the manipulation and analysis of these mathematical objects to solve complex systems of equations.

2. Why is Linear Algebra important?

Linear Algebra is important in many fields of science and engineering, including physics, computer science, economics, and statistics. It provides a foundation for understanding and solving problems in these areas by providing tools for modeling, analyzing, and interpreting data.

3. What is the difference between a matrix and a vector?

A matrix is a rectangular array of numbers or variables, while a vector is a one-dimensional array of numbers or variables. Matrices are used to represent linear transformations and systems of linear equations, whereas vectors are used to represent quantities with both magnitude and direction, such as velocity or force.

4. Can you explain the concept of matrix multiplication?

Matrix multiplication is a way of combining two or more matrices to create a new matrix. It involves multiplying the elements of one row of the first matrix by the corresponding elements in each column of the second matrix and then adding the products. The resulting matrix will have the same number of rows as the first matrix and the same number of columns as the second matrix.

5. How is Linear Algebra used in real-life applications?

Linear Algebra has numerous real-life applications, such as image and signal processing, data compression, computer graphics, and machine learning. It is also used in physics to model physical systems and in economics to analyze and predict economic trends. Additionally, Linear Algebra is used in engineering to design and optimize structures and systems.

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