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22.3: Basis Vectors

  • Page ID
    68046
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    Consider the following example. We claim that the following set of vectors form a basis for \(R^3\):

    \[B = \{(2,1, 3), (-1,6, 0), (3, 4, -10) \} \nonumber \]

    If these vectors form a basis they must be linearly independent and Span the entire space of \(R^3\)

    %matplotlib inline
    import matplotlib.pylab as plt
    import numpy as np
    import sympy as sym
    from urllib.request import urlretrieve
    sym.init_printing(use_unicode=True)
    urlretrieve('https://raw.githubusercontent.com/colbrydi/jupytercheck/master/answercheck.py', 
                'answercheck.py');
    Do This

    Create a \(3 \times 3\) numpy matrix \(A\) where the columns of \(A\) form are the basis vectors.

    #Put your answer to the above question here
    from answercheck import checkanswer
    
    checkanswer.matrix(A,'68b81f1c1041158b519936cb1a2e4d6b');
    Do This

    Using python, calculate the determinant of matrix \(A\).

    # Put your answer to the above question here. 
    Do This

    Using python, calculate the inverse of \(A\).

    # Put your answer to the above question here.
    Do This

    Using python, calculate the rank of \(A\).

    # Put your answer to the above question here.
    Do This

    Using python, calculate the reduced row echelon form of \(A\).

    # Put your answer to the above question here. 
    Do This

    Using the above \(A\) and the vector \(b=(1,3,2)\). What is the solution to \(Ax=b\)?

    #Put your answer to the above question here.
    from answercheck import checkanswer
    
    checkanswer.matrix(x,'8b0938260dfeaafc9f8e9fec0bc72f17');

    Turns out a matrix where column vectors are formed from basis vectors a lot of interesting properties and the following statements are equivalent.

    • The column vectors of \(A\) form a basis for \(R^n\)
    • \(|A| \neq 0\)
    • \(A\) is invertible.
    • \(A\) is row equivalent to \(I_n\) (i.e. it’s reduced row echelon form is \(I_n\))
    • The system of equations \(Ax=b\) has a unique solution.
    • \(rank(A) = n\)

    Not all matrices follow the above statements but the ones that do are used throughout linear algebra so it is important that we know these properties.


    This page titled 22.3: Basis Vectors is shared under a CC BY-NC 4.0 license and was authored, remixed, and/or curated by Dirk Colbry via source content that was edited to the style and standards of the LibreTexts platform.

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