Midterm 2 ================================================================

2.3        Sensitivity and Conditioning
2.3.1         Vector Norms
2.3.2         Matrix Norms
2.3.3         Matrix Condition Number
2.3.4         Error Bounds
2.3.5         Residual

5.6        Systems of Nonlinear Equations
5.6.1        Fixed Point Iteration
5.6.2        Newton's Method

7       Interpolation
7.1        Interpolation
7.2        Existence, Uniqueness and Conditioning
7.3        Polynomial Interpolation
7.3.1        Monomial Basis
7.3.2        Lagrange Interpolation
7.3.3        Newton Interpolation (including the divided differences)
7.3.5        Interpolating Continuous Functions (including error estimates)
7.4        Piecewise Polynomial Interpolation
7.4.2        Cubic Spline Interpolation
notes        splines.html : notes on splines
             spline.pdf   : derivation of solution method for splines
             bicubic.pdf  : formal description of 2D splines on regular lattice.
             -- all linked from either of the following:
                http://www-users.itlabs.umn.edu/classes/Spring-2008/csci5302/Notes/Local/splines.html
                https://www.cs.umn.edu/~boley/5302-08s/OffCampus/splines.html

8       Numerical Integration and Differentiation
8.1        Integration
8.3        Numerical Quadrature
8.3.1        Newton-Cotes Quadrature (i.e. using polynomial interpolation with
             equally spaced points)
8.3.5        Composite Quadrature
8.7        Richardson Extrapolation (not including Romberg Integration)

3       Linear Least Squares
3.1        Linear Least Squares Problems
3.2        Existence and Uniqueness
3.2.1         Normal Equations
3.2.2         Orthogonality and Orthogonal Projectors (only the first page)

6       Optimization (only the small part below)
(6.2.2)       Unconstrained Optimality Conditions [for this exam, you should
              know only how to compute the gradient and Hessian.  How these
              are related to optimality conditions will be covered later.)