Showing Linear Dependence In Exercises 53-56, show that the set is linearly dependent by finding a nontrivial linear combination vectors in the set whose sum is the zero vector. Then express one of the vectors in the set as a linear combinations of the other vectors in the set. S = { ( 1 , 2 , 3 , 4 ) , ( 1 , 0 , 1 , 2 ) , ( 1 , 4 , 5 , 6 ) }
Showing Linear Dependence In Exercises 53-56, show that the set is linearly dependent by finding a nontrivial linear combination vectors in the set whose sum is the zero vector. Then express one of the vectors in the set as a linear combinations of the other vectors in the set. S = { ( 1 , 2 , 3 , 4 ) , ( 1 , 0 , 1 , 2 ) , ( 1 , 4 , 5 , 6 ) }
Solution Summary: The author explains that the set is linearly dependent and expresses one of the vectors as a linear combination.
Showing Linear Dependence In Exercises 53-56, show that the set is linearly dependent by finding a nontrivial linear combination vectors in the set whose sum is the zero vector. Then express one of the vectors in the set as a linear combinations of the other vectors in the set.
Quantities that have magnitude and direction but not position. Some examples of vectors are velocity, displacement, acceleration, and force. They are sometimes called Euclidean or spatial vectors.
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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.
Chapter 4 Solutions
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