Transcription of MATH 320 LINEAR ALGEBRA - …
1 math 320 LINEAR ALGEBRA Izzet Co skun, MWF 9:00-9:50 423, to math 320! This course is an introduction to LinearAlgebra. LINEAR ALGEBRA is one ofthe great subjects of modern mathematics and an invaluable tool in many other disciplines ranging fromeconomics to computer science and physics to engineering. In this course we will explore solutions tolinear systems of equations, vector spaces and LINEAR webpage: :316 Taft HallOffice hours:MW 10-11, F 11-12 and by :The required text for this course is LINEAR ALGEBRA by Jim Hefferon available on line :Calculus I, II, III.
2 Some familiarity with writing proofs ishelpful, but not :There will be weekly homework, a mid-term and a final. The midterm and the homeworkwill count for 30 % of your grade each. The final exam will account for 40 % of your grade. In order topass the course, you must pass the final exam. The homeworks will be due Wednesdays in the beginningof class. No late homework will be accepted. You may collaborate on the homework problems, but youmust write your own solutions and properly acknowledge any help you receive from others.
3 I considerthe homework to be the most important part of this course. Anyone who misses more than two problemsets will receive a failing :The following is a tentative list of topics that will be covered in the course. Please read thematerial in the text book before 28 LINEAR systems of equationsChapter 1 Section 1 Aug 30 Gaussian EliminationChapter 1 Section 2 Sep 1 Gaussian EliminationChapter 1 Section 2 Sep 4No class: Labor DaySep 6 Reduced Echelon FormChapter 1 Section 3 Sep 8 ApplicationsChapter 1 TopicsSep 11 Vector SpacesChapter 2 Section 1 Sep 13 Vector SpacesChapter 2 Section 1 Sep 15 LINEAR IndependenceChapter 2 Section 2 Sep 18 BasesChapter 2 Section 3 Sep 20 DimensionChapter 2 Section 3 Sep 22 ApplicationsChapter 2 TopicsSep 25 HomomorphismsChapter 3 Section 1 Sep 27 IsomorphismsChapter 3 Section 112 math 320 LINEAR ALGEBRASep 29 Rank and kernelChapter 3 Section 2 Oct 2 Null Space and RangeChapter
4 3 Section 2 Oct 4 MatricesChapter 3 Section 3 Oct 6 MatricesChapter 3 Section 4 Oct 9 Change of basesChapter 3 Section 5 Oct 11 Gram-Schmidt OrthogonalizationChapter 3 Section 6 Oct 13 ProjectionsChapter 3 Section 6 Oct 16 DeterminantsChapter 4 Section 1 Oct 18 DeterminantsChapter 4 Section 1 Oct 20 DeterminantsChapter 4 Section 2 Oct 23 MIDTERMOct 25 DeterminantsChapter 4 Section 3 Oct 27 ApplicationsChapter 4 TopicsOct 30 EigenvaluesChapter 5 Section 1 Nov 1 EigenvectorsChapter 5 Section 2 Nov 3 EigenvectorsChapter 5 Section 2 Nov 6 EigenvectorsChapter 5 Section 2 Nov 8 DiagonalizationChapter 5 Section 3 Nov 10 DiagonalizationChapter 5 Section 3 Nov 13 Jordan Canonical FormChapter 5 Section 4 Nov 15 Jordan Canonical FormChapter 5 Section 4 Nov 17 Jordan Canonical FormChapter 5 Section 4 Nov 20 Symmetric matricesNov 22 Symmetric matricesNov 24No class.
5 ThanksgivingNov 27 Symmetric matricesNov 29 Hermitian matricesDec 1 Skew-Symmetric matricesDec 4 Skew-Symmetric matricesDec 6 ApplicationsDec 8 Applications
