## Elementary Linear Algebra: Applications Version, 11th EditionElementary Linear Algebra 11th edition gives an elementary treatment of linear algebra that is suitable for a first course for undergraduate students. The aim is to present the fundamentals of linear algebra in the clearest possible way; pedagogy is the main consideration. Calculus is not a prerequisite, but there are clearly labeled exercises and examples (which can be omitted without loss of continuity) for students who have studied calculus. |

### What people are saying - Write a review

User Review - Flag as inappropriate

DO NOT BUY THIS BOOK!! The book leaves a lot to be desired from a textbook. I bought the book outright for a class I that I had to have and I actually was able to learn more from Google than the textbook. The book is a total waste of time and money for any struggling student.

### Contents

CHAPTER 2 Determinants | 105 |

CHAPTER 3 Euclidean Vector Spaces | 131 |

CHAPTER 4 General Vector Spaces | 183 |

CHAPTER 5 Eigenvalues and Eigenvectors | 291 |

CHAPTER 6 Inner Product Spaces | 345 |

CHAPTER 7 Diagonalization and Quadratic Forms | 401 |

CHAPTER 8 General Linear Transformations | 447 |

CHAPTER 9 Numerical Methods | 491 |

CHAPTER 10 Applications of Linear Algebra | 527 |

APPENDIX A Working with Proofs | A-1 |

APPENDIX B Complex Numbers | A-5 |

Answers to Exercises | A-13 |

Index | 11 |

Index of Applications and Historical Topics | 25 |

### Common terms and phrases

angle augmented matrix axioms basis vectors calculate called coefﬁcients cofactor column space column vectors compute coordinate vector corresponding deﬁned definition denote det(A determine diagonalizable dot product eigenspace eigenvalues eigenvector entries equation Euclidean inner product example Exercise Set expressed factor False Figure ﬁnd ﬁrst following theorem Formula geometric graph harvesting inner product space integer invertible matrix iterations justify your answer least squares linear algebra linear combination linear operator linear system linear transformation linearly independent matrix transformation nonzero vector null space obtain one-to-one orthogonal projection pixel plane player points polynomial positive problem proof Prove quadratic form real numbers reduced row echelon result rotation row echelon form row space row vectors scalar multiplication solution solve square matrix standard basis standard matrix subspace symmetric symmetric matrix system Ax transition matrix True True/False values vector space vectors in Rn vectors v1 verify vertex xTAx zero