ࡱ> -/,yc }"bjbj** .FHSbHSbJ2 LLLLL```84\`$(j($ΊbɈLɈLLވLL*}eqiR0$Yvee&LɈɈL$ B :  MACROBUTTON MTEditEquationSection2 Equation Chapter 1 Section 1 SEQ MTEqn \r \h \* MERGEFORMAT  SEQ MTSec \r 1 \h \* MERGEFORMAT  SEQ MTChap \r 1 \h \* MERGEFORMAT Math 220 Review for the Final Exam Material on the Exam The exam will begin with warm-ups. You will need to interpret a quote using complete English sentences. The exam will be cumulative covering materials in chapters 1 to 6 as covered in class. It is a closed book, closed note exam. In addition to the material covered in the class, you are responsible for all of the basic facts you have learned since kindergarten. These include the facts that James Garfield was the President of the United States of America,  EMBED Equation.DSMT4 , and that 1/0 is undefined. You must be able to answer warm up questions and paraphrase quotes. Format It is a paper and pencil exam. You will need to show your work. You may use a graphing calculator (for the full exam). However, you may not use a symbolic calculator such as the TI-89 because they can do exact algebra (finding eigenvalues and an exact orthonormal basis). I may come around and check calculators to see what happens to be stored in their memory. You will have two hours for the exam, it will be around 12 questions and 2 proofs. Milkshakes? Ideas that may help with test prep Review the most recent material first. Make note cards for important formulas and definitions. Set aside once known. Rework examples from class and homework questions (in this order). Practice like you will play: without notes and with the clock running Study with a friend to have more fun. Look to online resources such as YouTube and the Khan Academy to fill in holes. Show up at least five minutes early for the exam. Course Objectives: The student will Solve systems using Gauss-Jordan elimination. Identify and orthogonalize the basis of a vector space. Apply matrix methods to model a data set using least squares regression. Calculate and interpret the eigenvalues and eigenvectors of a matrix. Identify, create, and apply linear transformations using matrix methods. Construct a mathematical proof. Notes on the sections (not necessarily exhaustive) Regarding Proofs You can expect two actual proof questions on the Final Exam. The first will be to show that a transformation is a linear transformation and/or to show that a space is a subspace. There may also be questions that ask you to explain some of the basic proof methods we have used. That is, you wouldnt actually prove anything, but rather explain the basic structure of a proof: Direct, Contradiction, If and only, if, Uniqueness, Induction, and Construction. The 2015 Final Exam 10 pages Warm ups and quote (as usual) Twelve questions (some with many parts) including 1 proof and 3 over new material. Calculator allowed throughout. Some questions may ask you to show work (though you could check on the calculator). Averages on past finals Winter 2015Winter 2016Winter 2019High99%96.3%107%Mean69.4%66.8%71.5%Median66.7%63.8%73.5% Common Pitfalls Parallelogram grid linear transformations What is P2? To show a transformation is linear, you must begin with an arbitrary element. Practice finding the null space so you can find eigenvectors. What happens if you have a column of zeros? Chapters 1 and 2 Matrix and vector vocabulary. Using Gauss-Jordan Elimination to solve systems of equations including interpreting the results. You must be able to do this by hand for a system of three equations and three unknowns (without a calculator). Distinguish between RREF and REF. Understand the rank of a matrix and its impact. Perform basic matrix algebra including addition, scalar multiplication, and matrix multiplication. You should be able to prove properties of these operations. Linear combinations You should be able to solve systems using a parallelogram grid. If a system has an infinite number of solutions, you should be able to write the solution in vector form using free variables. Understand linear transformations, the definitions, properties, and the relation between the function T and the matrix A. You should be able to prove claims about linear transformations. You should be comfortable with the ei notation for the standard basis vectors. You should be able to construct a transformation matrix by determining what the transformation does to the standard basis vectors. You should be able to work with linear transformations using a parallelogram grid. You should have a basic understanding of various geometric linear transformations including scaling, reflections, shear, rotations, and projections. You need to have the rotation matrix memorized. You may find it helpful to play with the animations in the e-book. Know the characterizations of invertible matrices. Chapter 3 (sections 1 and 2) Calculate determinants including knowing how to use row ops to find the determinant. Properties of the determinant. Chapter 4 Vector spaces and subspaces including examples Span, linear independence, bases, dimension, and coordinates for linear transformations. The basis of a linear space and of a subspace. Linear transformations, image, null space, rank, and nullity. Isomorphisms from vector spaces to Rn (see section 4.4). Finding the matrix of a linear transformation and using this matrix to find the image and null space. Chapter 5 Answer basic questions about diagonalization The characteristic polynomial and eigenvalues. The number of eigenvalues Algebraic and geometric multiplicity. Eigenvalues of triangular and diagonal matrices. Eigenspaces and eigenbases The geometric interpretation of eigenvalues and eigenvectors. Be able to find complex eigenvalues (w/o a calculator) and eigenvectors using technology. Understand and be able to diagonalize a matrix using an eigenbasis. Powers of diagonalizable matrices. Understand and be able to use complex eigenvalues to find a similar rotation-scaling matrix (2x2 case) Be able to work with dynamical systems with real and complex eigenvalues. Chapter 6 Orthonormal vectors and bases. The orthogonal projection including parallel and perpendicular components (and their notation). The formulas for  EMBED Equation.DSMT4  and  EMBED Equation.DSMT4 . The orthogonal complement and its properties. Know the Gram-Schmidt process and how to find the QR factorization. Orthogonal transformations and matrices. Orthogonal transformations preserve angles. Orthogonal transformations and the standard basis. Orthogonal matrices and their columns. The transpose of an orthogonal matrix. The matrix of an orthogonal projections. The normal equation of a system. Matrices and the least squared solution.     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