Course Archives Theoretical Statistics and Mathematics Unit
Course: Linear Algebra II
Instructor: Shreedhar Inamdar
Room: Second floor auditorium
Time: Currently offered
Syllabus
Past Exams

Syllabus:

Determinant of n-th order and its elementary properties, expansion by a row or column, statement of Laplace expansion, determinant of a product, statement of Cauchy- Binet theorem, inverse through classical adjoint, Cramers rule, determinant of a partitioned matrix, Idempotent matrices. Norm and inner product on Rn and Cn, norm induced by an inner product, Orthonormal basis, Gram-Schmidt orthogonalization starting from any finite set of vectors, orthogonal complement, orthogonal projection into a subspace, orthogonal projector into the column space of A, orthogonal and unitary matrices. Characteristic roots, relation between characteristic polynomials of AB and BA when AB is square, Cayley-Hamilton theorem, idea of minimal polynomial, eigenvectors, algebraic and geometric multiplicities, characterization of diagonalizable matrices, spectral representation of Hermitian and real symmetric matrices, singular value decomposition. Quadratic form, category of a quadratic form, use in classification of conics, Lagranges reduction to diagonal form, rank and signature, Sylvesters law, determinant criteria for n.n.d. and p.d. quadratic forms, Hadamards inequality, extrema of a p. d. quadratic form, simultaneous diagonalization of two quadratic forms one of which is p.d., simultaneous orthogonal diagonalization of commuting real symmetric matrices, square-root method.

Note: Geometric meaning of various concepts like subspace and flat, linear independence, projection, determinant (as volume), inner product, norm, orthogonality, orthogonal projection, and eigenvector should be discussed. Only finite-dimensional vector spaces to be covered.

Reference Texts:

(a) C. R. Rao: Linear Statistical Inference and its Applications.
(b) A. Ramachandra Rao and P. Bhimasankaram: Linear Algebra.
(c) K. Hoffman and R. Kunze: Linear Algebra.
(d) F. E. Hohn: Elementary Matrix Algebra.
(e) P. R. Halmos: Finite Dimensional Vector Spaces.
(f) S. Axler: Linear Algebra Done Right!
(g) H. Helson: Linear Algebra.
(h) R Bapat: Linear Algebra and Linear Models.
(i) R. A. Horn and C. R. Johnson: Matrix Analysis.
(j) M. Artin: Algebra.

Evaluation:
 Mid-term 30 marks Assignment 20 marks Final Exam 50 marks Total 100 marks

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Past Exams
Midterm
 23.pdf 24.pdf
Semestral
 22.pdf 23.pdf
Supplementary and Back Paper
 22.pdf 23.pdf

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[ Semester Schedule ][ Statmath Unit ] [Indian Statistical Institute]