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Describe the possible echelon forms of a nonzero \(3 \times 2\) matrix. Use the symbols \(\square, *\), and \(0\).

Short Answer

Expert verified

The possible echelon forms of a nonzero \(3 \times 2\) matrix are \(\left[ \begin{matrix} \square & * \\ 0 & \square \\ 0 & 0 \\ \end{matrix} \right]\), \(\left[ \begin{matrix} \square & * \\ 0 & 0 \\ 0 & 0 \\ \end{matrix} \right]\), and \(\left[ \begin{matrix} 0 & \square \\ 0 & 0 \\ 0 & 0 \\ \end{matrix} \right]\).

Step by step solution

01

Write the conditions for the echelon and reduced echelon forms

Check whether the provided matrix is in the reduced echelon form or just the echelon form for the given augmented matrices.

The matrix is in the echelon form if it satisfies the following conditions:

  • The nonzero rows should be positioned above the zero rows.
  • Each row's leading entry should be in the column to the right of the row above its leading item.
  • In each column, all items below the leading entry should be zero.

For the reduced echelon form, the matrix must follow the above conditions as well as some additional conditions as shown below:

  • Each column's components below the leading entry must be zero.
  • Each column's leading 1 must be the sole nonzero item.
02

Describe the first possible echelon form of the matrix

Consider the condition that nonzero rows should be stacked on top of rows with all zeros, and there should be a nonzero value in the leading entries in the column.

\(\left[ \begin{matrix} \square & * \\ 0 & \square \\ 0 & 0 \\ \end{matrix} \right]\)

03

Describe the second possible echelon form of the matrix

Consider the condition that nonzero rows should be stacked on top of rows with all zeros, and there should be a nonzero value in the leading entries in the column.

\(\left[ \begin{matrix} \square & * \\ 0 & 0 \\ 0 & 0 \\ \end{matrix} \right]\)

04

Describe the third possible echelon form of the matrix

Consider the condition that nonzero rows should be stacked on top of rows with all zeros and contain a single leading entry.

\(\left[ \begin{matrix} 0 & \square \\ 0 & 0 \\ 0 & 0 \\ \end{matrix} \right]\)

Thus, the possible echelon forms of a nonzero 3 x 2 matrix are \(\left[ \begin{matrix} \square & * \\ 0 & \square \\ 0 & 0 \\ \end{matrix} \right]\), \(\left[ \begin{matrix} \square & * \\ 0 & 0 \\ 0 & 0 \\ \end{matrix} \right]\), and \(\left[ \begin{matrix} 0 & \square \\ 0 & 0 \\ 0 & 0 \\ \end{matrix} \right]\).

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Most popular questions from this chapter

Find the general solutions of the systems whose augmented matrices are given in Exercises 10.

10. \(\left[ {\begin{array}{*{20}{c}}1&{ - 2}&{ - 1}&3\\3&{ - 6}&{ - 2}&2\end{array}} \right]\)

Let T be a linear transformation that maps \({\mathbb{R}^n}\) onto \({\mathbb{R}^n}\). Is \({T^{ - 1}}\) also one-to-one?

Suppose an experiment leads to the following system of equations:

\(\begin{aligned}{c}{\bf{4}}.{\bf{5}}{x_{\bf{1}}} + {\bf{3}}.{\bf{1}}{x_{\bf{2}}} = {\bf{19}}.{\bf{249}}\\1.6{x_{\bf{1}}} + 1.1{x_{\bf{2}}} = 6.843\end{aligned}\) (3)

  1. Solve system (3), and then solve system (4), below, in which the data on the right have been rounded to two decimal places. In each case, find the exactsolution.

\(\begin{aligned}{c}{\bf{4}}.{\bf{5}}{x_{\bf{1}}} + {\bf{3}}.{\bf{1}}{x_{\bf{2}}} = {\bf{19}}.{\bf{25}}\\1.6{x_{\bf{1}}} + 1.1{x_{\bf{2}}} = 6.8{\bf{4}}\end{aligned}\) (4)

  1. The entries in (4) differ from those in (3) by less than .05%. Find the percentage error when using the solution of (4) as an approximation for the solution of (3).
  1. Use your matrix program to produce the condition number of the coefficient matrix in (3).

Find the elementary row operation that transforms the first matrix into the second, and then find the reverse row operation that transforms the second matrix into the first.

30.\(\left[ {\begin{array}{*{20}{c}}1&3&{ - 4}\\0&{ - 2}&6\\0&{ - 5}&9\end{array}} \right]\), \(\left[ {\begin{array}{*{20}{c}}1&3&{ - 4}\\0&1&{ - 3}\\0&{ - 5}&9\end{array}} \right]\)

Use the accompanying figure to write each vector listed in Exercises 7 and 8 as a linear combination of u and v. Is every vector in \({\mathbb{R}^2}\) a linear combination of u and v?

8.Vectors w, x, y, and z

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