Spring 2016 CALENDAR
Math 2270-2, meets MWF

Week 1 
Jan 11 §1.1 
Linear systems

Jan 13 §1.2
Row reduction and echelon forms

Jan 15 §1.3
Vector equations

Week 2
Jan 18
Holiday, Martin Luther King Day

Jan 20 §1.4
The matrix equation Ax = b

Jan 22 §1.5
Solution sets of linear systems


Week 3
Jan 25 §1.6
Applications of linear systems

Jan 27 §1.7
Linear independence

Jan 29 §1.8
Linear transformations

Week 4
Feb 1 
§1.9 Matrix of a linear transformation

§1.10 optional, Linear models in business, science, and engineering

Feb 3 
§2.1 Matrix operations
§3.1 Determinants. Exercises 15-18, Sarrus' Rule.

Feb 5 
§2.2 Inverse of a matrix
§2.3 Characterization of invertible matrices

Week 5
Feb 8 
§2.4 Partitioned Matrices

Feb 10 
§2.5 Matrix factorization


Feb 12
§3.1 Introduction to determinants. Started in Week 4.
Project Deadline 1: Create or join a group

2.6 optional, The Leontief Input–Output Model
2.7 optional, Applications to Computer Graphics
Delayed §2.8 Subspaces of R^n
Delayed §2.9 Dimension and Rank

Week 6
Feb 15, Holiday: President's Day

Feb 17 
§3.2 Properties of determinants
§3.3 Cramer’s rule, volume and linear transformations

Feb 19
Exam 1

Week 7
Feb 22 
Summary of delayed section §2.8 Subspaces of R^n
§4.1 Vector spaces and subspaces

Feb 24 
§4.2 Null spaces, column spaces, and linear transformations.

Feb 26 
 Summary of delayed section §2.9 Dimension and Rank, §4.3 Linearly independent sets and bases, 

Week 8
Feb 29
§4.4 Coordinate Systems

Mar 2 
§4.5 The dimension of a vector space

Mar 4 
§4.6 Rank

Week 9
Mar 7 
§4.7 Change of basis

Mar 9 
§5.1 Eigenvectors and eigenvalues

Mar 11
Appendix B: Review of complex numbers
§4.8 optional, Applications to Difference Equations
§4.9 optional, Applications to Markov chains

Week 10
Mar 14 to 18 Spring Break

Week 11
Mar 21
§5.2 The characteristic equation

Mar 23 
§5.3 Diagonalization

Mar 25 
§5.4 Eigenvectors and linear transformations

Week 12
Mar 28 
§5.5 Complex eigenvalues

5.6 optional, Discrete Dynamical Systems
5.7 optional, Applications to differential equations
5.8 optional, Iterative Estimates for Eigenvalues

Mar 30 
§6.1 Inner product, length and orthogonality

Apr 1 
§6.2 Orthogonal sets
Project Deadline 2: Group leader submits project draft. Final copy due May 2.

Week 13
Apr 4 
§6.3 Orthogonal projections

Apr 6 
§6.4 The Gram–Schmidt process

Apr 8 
Exam 2

Week 14
Apr 11 
§6.5 Least-squares problems

6.6 optional, Application to linear models
6.7 optional, Inner product spaces
6.8 optional, Applications of Inner Product Spaces

Apr 13 
§7.1 Diagonalization of symmetric matrices

Apr 15 
§7.2  Quadratic Forms

Week 15
Apr 18 
§7.3 Constrained Optimization

Apr 20 
§7.4 The singular value decomposition

§7.5 optional

Apr 22
Presentation of projects
Week 16
Apr 25, Presentation of projects (last class)
Apr 26, Last office hours 113 JWB
Apr 26, Final Exam Review, to be scheduled
Apr 27 Reading Day
Apr 28, 7:30am to 10:00am, Final Exam regular classroom