Each statement in Exercises 39—44 is either true (in all cases) or false (for at least one example). If false, construct a specific example to show that the statement is not always true. Such an example is called a counterexample to the statement. If a statement is true, give a justification. (One specific example cannot explain why a statement is always true. You will have to do more work here than in Exercises 21—28.) 43. (T/F-C) If v 1 , … , v 4 are in R 4 and v 1 , v 2 , v 3 is linearly dependent, then v 1 , v 2 , v 3 , v 4 is also linearly dependent.
Each statement in Exercises 39—44 is either true (in all cases) or false (for at least one example). If false, construct a specific example to show that the statement is not always true. Such an example is called a counterexample to the statement. If a statement is true, give a justification. (One specific example cannot explain why a statement is always true. You will have to do more work here than in Exercises 21—28.) 43. (T/F-C) If v 1 , … , v 4 are in R 4 and v 1 , v 2 , v 3 is linearly dependent, then v 1 , v 2 , v 3 , v 4 is also linearly dependent.
Solution Summary: The author evaluates whether the given statement is true or false.
Each statement in Exercises 39—44 is either true (in all cases) or false (for at least one example). If false, construct a specific example to show that the statement is not always true. Such an example is called a counterexample to the statement. If a statement is true, give a justification. (One specific example cannot explain why a statement is always true. You will have to do more work here than in Exercises 21—28.)
43. (T/F-C) If
v
1
,
…
,
v
4
are in
R
4
and
v
1
,
v
2
,
v
3
is linearly dependent, then
v
1
,
v
2
,
v
3
,
v
4
is also linearly dependent.
I want to learn this topic l dont know anything about it
Solve the linear system of equations attached using Gaussian elimination (not Gauss-Jordan) and back subsitution.
Remember that:
A matrix is in row echelon form if
Any row that consists only of zeros is at the bottom of the matrix.
The first non-zero entry in each other row is 1. This entry is called aleading 1.
The leading 1 of each row, after the first row, lies to the right of the leading 1 of the previous row.
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