SET MATHEMATICAL SCIENCE SYLLABUS 2021


Initially, the paper pattern consisted of 3 papers (Paper I, II, and III), but as of after 2019, the updated exam pattern is of 2 papers (Paper I and II).

The paper II and III subjective syllabus content is merged to form paper II. Paper I is of general nature, intended to assess the teaching/research aptitude of the candidate. It consists of 50 compulsory MCQs of 2 marks each. This paper is for 1 hour.

Paper-II will contain 100 compulsory MCQs of two marks each from the Mathematical Science subject and the duration of this paper has been made as two hours (120 minutes).

PAPER I

Teaching Aptitude

Teaching: Concept, Objectives, Levels of teaching (Memory, Understanding and Reflective), Characteristics and basic requirements.

Learner's characteristics: Characteristics of adolescent and adult learners(Academic, Social, Emotional and Cognitive), Individual differences.

Factors affecting teaching related to: Teacher, Learner, Support material,Instructional facilities, Learning environment and Institution.

Methods of teaching in Institutions of higher learning: Teacher centred vs.Learner centred methods; Off-line vs. On-line methods (Swayam,Swayamprabha, MOOCs etc.).

Teaching Support System: Traditional, Modern and ICT based.

Evaluation Systems: Elements and Types of evaluation, Evaluation in Choice Based Credit System in Higher education, Computer based testing, Innovations in evaluation systems.

Research Aptitude

Research: Meaning, Types, and Characteristics, Positivism and Post- positivistic approach to research.

Methods of Research: Experimental, Descriptive, Historical, Qualitative and Quantitative methods.

Steps of Research.

Thesis and Article writing: Format and styles of referencing.

Application of ICT in research.

Research ethics.

Comprehension

A passage of text be given. Questions be asked from the passage to be answered.

Communication

Communication: Meaning, types and characteristics of communication.

Effective communication: Verbal and Non-verbal, Inter-Cultural and group communications, Classroom communication.

Barriers to effective communication.

Mass-Media and Society.

Mathematical Reasoning and Aptitude

Types of reasoning.

Number series, Letter series, Codes and Relationships.

Mathematical Aptitude (Fraction, Time & Distance, Ratio, Proportion and Percentage, Profit and Loss, Interest and Discounting, Averages etc.).

Data Interpretation

Sources, acquisition and classification of Data.

Quantitative and Qualitative Data.

Graphical representation (Bar-chart, Histograms, Pie-chart, Table-chart and Line-chart) and mapping of Data.

Data Interpretation.

Data and Governance.

Logical Reasoning

Understanding the structure of arguments: argument forms, structure of categorical propositions, Mood and Figure, Formal and Informal fallacies, Uses of language, Connotations and denotations of terms, Classical square of opposition.

Evaluating and distinguishing deductive and inductive reasoning.

Analogies.

Venn diagram: Simple and multiple use for establishing validity of arguments.

Indian Logic: Means of knowledge.

Pramanas: Pratyaksha (Perception), Anumana (Inference), Upamana (Comparison), Shabda (Verbal testimony), Arthapatti (Implication) and Anupalabddhi (Non-apprehension).

Structure and kinds of Anumana (inference), Vyapti (invariable relation), Hetvabhasas (fallacies of inference).

Information and Communication Technology (ICT)

ICT: General abbreviations and terminology.

Basics of Internet, Intranet, E-mail, Audio and Video-conferencing.

Digital initiatives in higher education.

ICT and Governance.

Higher Education System

Institutions of higher learning and education in ancient India.

Evolution of higher learning and research in Post Independence India.

Oriental, Conventional and Non-conventional learning programmes in India.

Professional, Technical and Skill Based education.

Value education and environmental education.

Policies, Governance, and Administration.

People, Development and Environment

Development and environment: Millennium development and Sustainable development goals.

Human and environment interaction: Anthropogenic activities and their impacts on environment.

Environmental issues: Local, Regional and Global; Air pollution, Water pollution, Soil pollution, Noise pollution, Waste (solid, liquid, biomedical, hazardous, electronic), Climate change and its Socio-Economic and Political dimensions.

Impacts of pollutants on human health.

Natural and energy resources: Solar, Wind, Soil, Hydro, Geothermal, Biomass, Nuclear and Forests.

Natural hazards and disasters: Mitigation strategies.

Environmental Protection Act (1986), National Action Plan on Climate Change, International agreements/efforts -Montreal Protocol, Rio Summit, Convention on Biodiversity, Kyoto Protocol, Paris Agreement, International Solar Alliance.

PAPER II

General Information : Units 1, 2, 3 and 4 are compulsory for all candidates. Candidates with Mathematics background may omit units 10-14 and units 17,18. Candidates with Statistics background may omit units 6,7,9,15 and 16. Adequate alternatives would be given for candidates with O.R. background.

1. Basic Concepts of Real and Complex Analysis

Sequences and series, Continuity, Uniform continuity, Differentiabilty, Mean Value Theorem, Sequences and series of functions, Uniform convergence, Riemann integral - definition and simple properties

Algebra of complex numbers, Analytic functions, Cauchy’s Theorem and integral formula, Power series, Taylor’s and Laurent’s series, Residues, Contour integration.

2. Basic Concepts of Linear Algebra

Space of n-vectors

Linear dependence

Basis, Linear transformation

Algebra of matrices

Rank of a matrix

Determinants

Linear equations

Quadratic forms

Characteristic roots and vectors.

3. Basic Concepts of Probability

Sample space, Discrete probability, Simple theorems on probability, Independence of events, Bayes Theorem, Discrete and continuous random variables, Binomial, Poisson and Normal distributions

Expectation and moments, Independence of random variables, Chebyshev’s inequality.

4. Linear Programming Basic Concepts

Convex sets, Linear Programming Problem (LPP)

Examples of LPP

Hyperplane, open and closed Half-spaces

Feasible, basic feasible and optimal solutions

Extreme point and graphical method.

5. Real Analysis

Finite, countable and uncountable sets, Bounded and unbounded sets, Archimedean property, ordered field, completeness of R, Extended real number system, limsup and liminf of a sequence, the epsilon-delta definition of continuty and convergence, the algebra of continuous functions, monotonic functions, types of discontinuties, infinite limits and limits at infinity, functions of bounded variation

elements of metric spaces.

6. Complex Analysis

Riemann Sphere and Stereographic projection

Lines, circles, crossratio

Mobius transformations, Analytic functions, Cauchy-Riemann equations, line integrals, Cauchy’s theorem, Morera’s theorem, Liouville’s theorem, integral formula, zero-sets of analytic functions, exponential, sine and cosine functions, Power siries representation, Classification of singularities, Conformal mapping.

7. Algebra

Group

subgroups

Normal subgroups

Quotient Groups

Homomorphisms

Cyclic Groups

Permutation Groups

Cayley’s Theorm

Rings

Ideals

Integral Domains

Fields

Polynomial Rings.

8. Linear Algebra

Vector spaces, subspaces, quotient spaces, Linear indepenence, Bases, Dimension

The algebra of linear Transformations, kernal, range, isomorphism, Matrix Representation of a linear transormation, change of bases, Linear functionals, dual space, projection, determinant function, eigenvalues and eigen vectorsCayley-Hamilton Theorem,Invariant Sub-spaces, Canonical Forms : diagonal form, Triangular form, Jordan Form

Inner product spaces.

9. Differential Equations

First order ODE, singular solutions initial value Problems of First Order ODE, General theory of homogeneous and non-homogeneous Linear ODE, Variation of Paraneters

Lagrange’s and Charpit’s methods of solving First order Partial Differental Equations

PDE’s of higher order with constant coefficients.

10. Data Analysis Basic Concepts

Graphical representation, measures of central tendency and dispersion

Bivariate data correlation and regression

Least squares-polynomial regression, Applications of normal distribution.

11. Probability

Axiomatic definition of probability

Random variables and distribution functions (univariate and multivariate); expectation and moments; independent events and independent random variables; Bayes theorem; marginal and conditional distribution in the multivariate case, covariance matrix and correlation coefficients (product moment, partial and multipal), regression

Moment generating functions, characteristic functions; probability inequalities (Tehebyshef, Markov, Jensen)

Convergence in probability and in distribution; weak law of large numbers and central limit theorem for independent indentically distributed random variables with finite variance.

12. Probability Distribution

Bemoulli, Binomial, Multinomial. Hypergeomatric, Poisson, Geometric and Negative binomial distributions, Uniform, exponential, Cauchy, Beta, Gamma, and normal (univariate and multivariate) distributions Transformations of random variables; sampling distributions

t, F and chi-square distributions as sampling distributions, as sampling distributions, Standard errors and large sample distributions

Distribution of order statistics and range.

13. Theory of Statistics

Methods of estimation : maximum likelihood method, method of moments, minimum chi-square method, least- squares method

Unbiasedness, efficiencey, consistency

Cramer-Rao inequality

Sufficient, Statistics

Rao-Blackwell theorem

Uniformly minimum variance unbiased estimators

Estimation by confidence intervals

Tests of hypotheses : Simple and composite hypotheses, two types of errors, critical region, randomized test, power function, most powerful and uniformly most powerful tests

Likelihood-ratio tests. Wald’s sequential probability ratio test.

14. Statistical Methods and Data Analysis

Tests for mean and variance in the normal distribution : one-population and two-population cases; related confidence intervals

Tests for product moment, partial and multiple correlation coefficients; comparison of k linear regressions

Fitting polynomial regression; related test Analysis of discrete date: chi-square test of goodness of fit, contingency tables

Analysis of variance : one-way and two-way classification (equal number of observations per cell)

Large sample tests through normal approximation

Nonparametric tests : sign test, Median test, Mann-Whitney test, Wilcoxon test for one and two-samples, rank correlation and test of independence.

15. Operational Research Modelling

Definition and scope of Operational Research

Different types of models

Replacement models and sequencing theory, Inventory problems and their analytical structure

Simple deterministic and stochastic models of inventory control

Basic characteristics of queueing system, different performance measures, steady state solution of Markovian queueing models: M/M/1, M/M/1 with limited waiting space M/M/C, M/M/C with limited waiting space.

16. Linear Programming

Linear Programming, Simplex method, Duality in linear programming

Transformation and assignment problems

Two person-zero sum games

Equivalence of rectangular game and linear programming.

17. Finite Population

Sampling Techniques and Estimation: Simple random sampling with and without replacement

Stratified sampling; allocation problem; systematic sampling Two stage sampling

Related estimation problems in the above cases.

18. Design of Experiments

Basic principles of experimental design

Randomisation structure and analysis of completely randomised, randomised blocks and Latin-square designs

Factorial experiments

Analysis of 2n factorial experiments in randomised blocks

PAPER III

Real Analysis

Riemann integrable functions; improper integrals, their convergence and uniform convergence

Eulidean space R", Bolzano-Weierstrass theorem, compact Subsets of R”, Heine-Borel T\theorem, Fourier series

Continuity of functions on R", Differentiability of F:R”-Rm

Properties of differential, partial and directional derivatives, continuously differentiable functions

Taylor’s series. Inverse function theorem, Implieit function theorem

Integral functions, line and surface integrals, Green’s theorem, Stoke’s theorem.

2. Complex Analysis

Cauchy’s theorem for convex regions

Power series representation of Analtic functions

Liouville’s theorem, Fundamental theorem of algebra Riemann’s theorem on removable singularities, maximum modulus principle

Schwarz Iemma, Open Mapping theorem, Casorattl-Weierstrass-theorem, Weierstrass’s theorem on uniform convergence on compact sets, Bilinear transformations, Multivalued Analytic Functions, Riemann Surfaces.

3. Algebra

Symmetric groups

Alternating groups

Simple groups

Rings

Maximal Ideals

Prime Ideals

Integral domains Euclidean domains

principal Ideal domains

Unique Factorisation domains

quotient fileds

Finite fields

Algebra of Linear Transformations

Reduction of matrices to Canonical Forms

Inner Product Spaces

Orthogonality

Quadratic Forms

Reduction of quadratic forms.

4. Advanced Analysis

Elements of Metric Spaces

Convergence

continuity

compactness

Connectedness

Weierstrass’s approximation Theorem

Completeness

Bare category theorem

Labesgue measure

Labesgue Integral

Differentiation and Integration.

5. Advanced Algebra

Conjugate elements and class equations of finite groups, Sylow theorems, solvable groups, Jordan Holder Theorem, Direct Products, Structure Theorem for finite abelian groups, Chain conditions on Rings

Characteristic of Field, Field extensions, Elements of Galois theory, solvability by Raducals, Ruler and compass construction.

6. Functional Analysis

Banach Spaces Hahn-Banach Theorem, Open mapping and closed Graph Theorems

Principal of Uniform boundedness, Boundedness and continuity of Linear Transformations, Dual Space, Embedding in the second dual, Hilbert Spaces, Projections

Orthonormal Basis, Riesz-representation theorem, Bessel’s Inequality, parsaval’s identity, self adjoined operators, Normal Operators.

7. Topology

Elements of Topological Spaces, Continuity, convergence, Homeomorphism, Compactness, Connectedness, Separation Axioms, First and Second Countability, Separability, Subspaces, Product Spaces, quotient spaces

Tychonoft’s Theorem, Urysohn’s Metrization theorem, Homotopy and Fundamental Group.

8. Discrete Mathematics

Partially ordered sets

Lattices

Cornplete Lattices

Distrbutive lattices

Complements

Boolean Algebra

Boolean Expressions

Application to switching circuits

Elements of Graph Theory

Eulerian and Hamiltonian graphs

planar Graphs

Directed Graphs

Trees

Permutations and Combinations

Pigeonhole principle

principle of Inclusion and Exclusion

Derangements.

9. Ordinary and partial Differential Equations

Existence and Uniqueness of solution dy/dx = f (x,y) Green’s function

sturm Liouville Boundary Value Problems

Cauchy Problems and Characteristics

Classification of Second Order PDE

Separation of Variables for heat equation

wave equation and Laplace equation

Special functions.

10. Number Theory

Divisibility; Linear diophantine equations

Congruences

Quadratic residues; Sums of two squares, Arithmatic functions Mu, Tau, and Signa (and ).

11. Machanics

Generalise coordinates

Lagranges equation

Hamilton’s cononical equations

Variational Principles-Hamilton’s pronciples and plrinciples of least action

Two dimensional motion of rigid bodies

Euler’s dynamical equations for the motion of rigid body

Motion of a rigid body about an axis

Motion about revolving axes.

12. Elasticity

Analysis of strain and stress, strain and stress tensors;

Geometrical representation

Compatibility conditions

Strain energy function

Constritutive relations

Elastic solids “Hookes law

Saint-Venant’s principle, Equations of equilibrium

Plane problem-Airy’s stress function vibrations of elastic, cylindrical and spherical media.

13. Fluid Mechanics

Equation of continuity in fluid motion

Euler’s equations of motion for perfect fluids

Two dimensional motion complex potential

Motion of sphere in perfect liquid and montion of liquid past a sphere; vorticity

Navier-Stokes’s equations for viscous flows- some exact solutions.

14. Differetial Geometry

Space curves-their curvature and torsion

Serret Frehat Formula

Fundamental theorem of space curves

Curves on sirfaces

First and second fundamental form

Gaussian curvatures

Principal directions and principal curvatures

Goedesics, Fundamental equations of surface theory.

15. Calculus of Variations

Linear functionals, minimal functional theorem, general variation of a functional, Euler-Lagrange equation

Variational methods of boundary value problems in ordinary and partial differential equations.

16. Linear Integral Equations

Linear Integral Equations of the first and second kind of Fredholm and Volterra type

solution by successive substitutions and successive approximations

Solution of equations with separable kernels

The Fredholm Alternative

Holbert-Schmidt theory for symmetric kernels.

17. Numerical analysis

Finite differences, Interpolation

Numerical solution of algebric equation

Iteration

Newton-Raphason Method

Solution on Linear system

Direct method

Gauss elminaiton method

Matrix-Inversion eigenvalue problems

Numerical differentiation and integration

Numerical solution of ordinary differential equation

iteration method, Picard’s method , Euler’s method and improved Euler’s method.

18. Integral Transform

Laplace transform

Transform of elementary functions, Transform of Derivatives, Inverse Transform, Convolution Theorem, Applications, Ordinary and Partial differential equations

Fourier transform

sine and cosine transform, Inverse Fourier Transform, Application to ordinary and partial differential equations.

19. Mathematical Programming

Revised simplex method, Dual simplex method, Sensitivity analysis and parametric linear programming

Kuhn-Tucker conditions of optimality

Quadratic programming; methods due to Beale, Wofle and Vandepanne, Duality in quadratic programmming, self duality, Integer programming.

20. Measure Theory

Measurable and measure spaces : Extension of measures,signed measures, Jordan-Hahn decomposition theorems

Integratiuon, monotone convergence theorem, Fatou’s lemma, dominaated convergence theorem

Absolute continuity, Radon Nikodym theorem, Product measures, Fubini's theorem.

21. Probability

Sequences of events and random variables: Zero-one laws of Borel and Kolmogorov

Almost sure convergence, convergence in mean square, Khintchine’s weak law of large numbers; Kolmogorov’s inequality, strong law of large numbers

Convergence of series of random variables, three-series criterion

Central limit theorems of Liapounov and Lindeberg-Feller

Conditional expectation, martingales.

22. Distribution Theory

Properties of distribution functions and characteristic functions; continuty theorem, inversion formula, Representation of distribution function as a mixture of discrete and continuous distribution functions; Convolutions, marginal and conditional distributions of bivariate discrete and continuous distributions

Relations between characteristic functions and moments; Moment inequalities of Holder and Minkowski.

23. Statistical Inference and Decision Theory

Statistical decision problem : non-randomized, mixed and randomized decision rules; risk function admissibility, Bayes rules, minimax rules, least favourable distributions, complete class and minimal complete class. Decision problem for finite parameter space. Convex loss function. Role of sufficiency

Admissible, Bayes and minimax estimators; illustrations

Unbiasedness

UMVU estimators

Families of distributons with monotone likelihood property, exponential family of distributions

Test of a simple hypothesis against a simple alternative from decision-theoretic viewpoint

Tests with Neyman structure

Uniformly most powerful unbiased tests

Locally most powerful tests

Inference on location and scale parameters; estimation and tests

Equivariant estimators

Invariance in hypothesis testing.

24. Large sample statistical methods

Various modes of convergence

Op and op, CLT, Sheffe’s theorem, Polya’s theorem and Slutsky’s theorem

Transformation and variance stabilizing formula

Asymptotic disribution of function of sample moments

Sample quantiles

Order statistics and their functions

Tests on correlations, coefficient of variation, skewness and kurtosis

Pearson Chi-square, contingency Chi-square and likelihood ratio statistics

U-statistics consistency of Tests

Asymptotic relative efficiency.

25. Multivariate Statistical Analysis

Singular and non-singular multivariate distributions

Characteristics functions

Multivariate normal distributions, margrinal and conditional distributions; distribution of linear forms, and quadratic forms, Cochran’s theorem

Inference on parameters of multivariate normal distributions, one-population and two population cases

wishart distribution

Hotellings T2, Mahalanobis D2 Discrimination analysis, Principal components, Canonical correlations, Cluster analysis.

26. Linear Models and Regression

Standard Gauss-Markov models; Estimability of parameters; best linear unbiased extimates(BLUE); Method of least squares and Gauss-Markovtheorem; Variance-covariance matrix of BLUES

Tests of linear hypothesis; One-way and two-way classifications

Fixed, random and mixed effects models (two-way classifications only); variance components, Bivariate and multiple linear regression; Polynomial regression; use of ortheogonal polynomials

Analysis of covarance

Linear and nonlinear regression outliers.

27. Sample Surveys

Sampling with varying probability of selection, Hurwitz-Thompson estimator; PPS sampling: Double sampling

Cluser sampling

Non-sampling errors: Interpentrating samples

Multiphase sampling

Ratio and regession methods of estimation.

28. Design of Experiments

Factorial experiments, confounding and fractional replication

Split and strip plot designs; Quasi-Latin square designs; Youden square

Design for study of response surfaces; first and second order designs

Incomplete block designs; Balanced, connectedness and orthogonality, BIBD with recovery of inter-block information PBIBD with 2 associate classes

Analysis of series of experiments, esimation of residual effects

Construction of orthogonal-Latin squares, BIB designs, and confounded factorial designs

Optimality criteria for experimental designs.

29. Time-Series Analysis

Discrete-parameter stochastic processes; strong and weak stationarity; autocovariance and autocorrelation

Moving average, autoregressive, autoregressive moving average and autoregressive intgegfrated moving average processes

Box-Jenkins models

Estimation of the parameters in ARIMA models; forecasting

Periodogram and correlogram analysis.

30. Stochastic Proceses

Markov chains with finite and countable state space, classification of states, limiting behaviour of n-step transition probabilities, stationary distribution; branching processes; Random walk; Gambler’s ruin

Markov processes in continuous time; Poisson processes, birth and death processes, Wiener process.

31. Demography and Vital Statistics

Measures of fertility and mortality, period and Cohort measures

Life tables and its applications; Methods of construction of abridged life tables

Application of stable population theory to estimate vital rates

Popultion projetions

Stochastic models of fertility and reproduction.

32. Industrial Statistics

Control charts for variables and attributes; Acceptance sampling by attribites; single, double and sequential sampling plans; OC and ASN functions, AOQL and ATI; Acceptance sampling by varieties

Tolerance limits Reliability analysis: Hazard function, distribution with DFR and IFR; Series and parallel systems

Life testing experiments.

33. Inventory and Queueing theory

Inventory (S,s) policy periodic review models with stochastic demand

Dynamic inventory models

Probabilistic re-order point, lot size inventory system with and without lead time

Distribution free analysis

Solution of inventory problem with unknown density function

Warehousing problem

Queues: Imbedded markov chain method to obtain steady state solution of M/G/1, G/M/1 and M/D/C, Network models

Machine maintenance models

Design and control of queueing systems.

34. Dynamic Programming and Marketing

Nature of dynamic programming, Deterministic processes, Non-sequential discrete optimisation-allocation problems, assortment problems

Sequential discrete optimisation long-term planning problems, multi stage production processes

Functional approximations

Marketing systems, application of dynamic programming to marketing problems

Introduction of new product, objective in setting market price and its policies, purchasing under Fluctuating prices, Advertising and promotional decisions, Brands swiching analysis, Distribution decisions.

Candidates should have to attend Both Paper I and Paper II. All questions are compulsory. Paper I is common for all subjects. Which contains language both English and Tamil. Questions in paper II covers the entire subject. The syllabus is equivalent to UCG NET. Candidates can also refer UGC NET syllabus official link given at the end of the post.

S. No SYLLABUS
1 Mathematics
2 Applied Mathematics
3 Statistics
4 Applied Statistics
5 Mathematics with Computer Science

All students are expected to answer questions from Unit I. Students in mathematics are expected to answer additional question from Unit II and III. Students with in statistics are expected to answer additional question from Unit IV.

S. No UNIT - 1
1 Analysis: Elementary set theory, finite, countable and uncountable sets, Real number system as a complete ordered field, Archimedean property, supremum, infimum.
2 Sequences and series, convergence, limsup, liminf.
3 Bolzano Weierstrass theorem, Heine Borel theorem.
4 Continuity, uniform continuity, differentiability, mean value theorem.
5 Sequences and series of functions, uniform convergence.
6 Riemann sums and Riemann integral, Improper Integrals.
7 Monotonic functions, types of discontinuity, functions of bounded variation, Lebesgue measure, Lebesgue integral.
8 Functions of several variables, directional derivative, partial derivative, derivative as a linear transformation, inverse and implicit function theorems.
9 Metric spaces, compactness, connectedness. Normed linear Spaces. Spaces of continuous functions as examples.
10 Linear Algebra: Vector spaces, subspaces, linear dependence, basis, dimension, algebra of linear transformations.
11 Algebra of matrices, rank and determinant of matrices, linear equations.
12 Eigenvalues and eigenvectors, Cayley-Hamilton theorem.
13 Matrix representation of linear transformations. Change of basis, canonical forms, diagonal forms, triangular forms, Jordan forms.
14 Inner product spaces, orthonormal basis.
15 Quadratic forms, reduction and classification of quadratic forms
S. No UNIT - 2
1 Complex Analysis: Algebra of complex numbers, the complex plane, polynomials, power series, transcendental functions such as exponential, trigonometric and hyperbolic functions. Analytic functions, Cauchy-Riemann equations.
2 Contour integral, Cauchy's theorem, Cauchy's integral formula, Liouville's theorem, Maximum modulus principle, Schwarz lemma, Open mapping theorem.
3 Taylor series, Laurent series, calculus of residues.
4 Conformal mappings, Mobius transformations.
5 Algebra: Permutations, combinations, pigeon-hole principle, inclusion-exclusion principle, derangements.
6 Fundamental theorem of arithmetic, divisibility in Z, congruences, Chinese Remainder Theorem, Euler's - function, primitive roots.
7 Groups, subgroups, normal subgroups, quotient groups, homomorphisms, cyclic groups, permutation groups, Cayley's theorem, class equations, Sylow theorems.
8 Rings, ideals, prime and maximal ideals, quotient rings, unique factorization domain, principal ideal domain, Euclidean domain.
9 Polynomial rings and irreducibility criteria.
10 Fields, finite fields, field extensions, Galois Theory.
11 Topology: basis, dense sets, subspace and product topology, separation axioms, connectedness and compactness.
S. No UNIT - 3
1 Ordinary Differential Equations (ODEs):Existence and uniqueness of solutions of initial value problems for first order ordinary differential equations, singular solutions of first order ODEs, system of first order ODEs.
2 General theory of homogenous and non-homogeneous linear ODEs, variation of parameters, Sturm-Liouville boundary value problem, Green's function.
3 Partial Differential Equations (PDEs):Lagrange and Charpit methods for solving first order PDEs, Cauchy problem for first order PDEs.
4 Classification of second order PDEs, General solution of higher order PDEs with constant coefficients, Method of separation of variables for Laplace, Heat and Wave equations.
5 Numerical Analysis : Numerical solutions of algebraic equations, Method of iteration and Newton-Raphson method, Rate of convergence, Solution of systems of linear algebraic equations using Gauss elimination and Gauss-Seidel methods, Finite differences, Lagrange, Hermite and spline interpolation, Numerical differentiation and integration, Numerical solutions of ODEs using Picard, Euler, modified Euler and Runge-Kutta methods
6 Calculus of Variations: Variation of a functional, Euler-Lagrange equation, Necessary and sufficient conditions for extrema.
Variational methods for boundary value problems in ordinary and partial differential equations.
7 Linear Integral Equations: Linear integral equation of the first and second kind of Fredholm and Volterra type, Solutions with separable kernels. Characteristic numbers and eigenfunctions, resolvent kernel.
8 Classical Mechanics: Generalized coordinates, Lagrange's equations, Hamilton's canonical equations, Hamilton's principle and principle of least action, Two-dimensional motion of rigid bodies, Euler's dynamical equations for the motion of a rigid body about an axis, theory of small oscillations.
S. No UNIT - 4
1 Descriptive statistics, exploratory data analysis
2 Sample space, discrete probability, independent events, Bayes theorem. Random variables and distribution functions (univariate and multivariate); expectation and moments. Independent random variables, marginal and conditional distributions. Characteristic functions. Probability inequalities (Tchebyshef, Markov, Jensen). Modes of convergence, weak and strong laws of large numbers, Central Limit theorems (i.i.d. case).
3 Markov chains with finite and countable state space, classification of states, limiting behaviour of n-step transition probabilities, stationary distribution, Poisson and birth-and-death processes.
4 Standard discrete and continuous univariate distributions. sampling distributions, standard errors and asymptotic distributions, distribution of order statistics and range.
5 Methods of estimation, properties of estimators, confidence intervals. Tests of hypotheses: most powerful and uniformly most powerful tests, likelihood ratio tests. Analysis of discrete data and chi-square test of goodness of fit. Large sample tests.
6 Simple nonparametric tests for one and two sample problems, rank correlation and test for independence. Elementary Bayesian inference.
7 Gauss-Markov models, estimability of parameters, best linear unbiased estimators, confidence intervals, tests for linear hypotheses. Analysis of variance and covariance. Fixed, random and mixed effects models. Simple and multiple linear regression. Elementary regression diagnostics. Logistic regression.
8 Multivariate normal distribution, Wishart distribution and their properties. Distribution of quadratic forms. Inference for parameters, partial and multiple correlation coefficients and related tests. Data reduction techniques: Principle component analysis, Discriminant analysis, Cluster analysis, Canonical correlation.
9 Simple random sampling, stratified sampling and systematic sampling. Probability proportional to size sampling. Ratio and regression methods.
10 Completely randomized designs, randomized block designs and Latin-square designs. Connectedness and orthogonality of block designs, BIBD. 2K factorial experiments: confounding and construction.
11 Hazard function and failure rates, censoring and life testing, series and parallel systems.
12 Linear programming problem, simplex methods, duality. Elementary queuing and inventory models. Steady-state solutions of Markovian queuing models: M/M/1, M/M/1 with limited waiting space, M/M/C, M/M/C with limited waiting space, M/G/1.

General Information : Units 1, 2, 3 and 4 are compulsory for all candidates. Candidates with Mathematics background may omit units 10-14 and units 17,18. Candidates with Statistics background may omit units 6,7,9,15 and 16. Adequate alternatives would be given for candidates with O.R. background

S. No PAPER - II
1 Basic Concepts of Real and Complex Analysis : sequences and series, Continuity, Uniform continuity, Differentiabilty, Mean Value Theorem, Sequences and series of functions, Uniform convergence, Riemann integral - definition and simple properties. Algebra of complex numbers, Analytic functions, Cauchy's Theorem and integral formula, Power series, Taylor's and Laurent's series, Residues, Contour integration
2 Basic Concepts of Linear Algebra : Space of n-vectors, Linear dependence, Basis, Linear transformation, Algebra of matrices, Rank of a matrix, Determinants, Linear equations, Quadratic forms, Characteristic roots and vectors.
3 Basic Concepts of Probability : Sample space, Discrete probability, Simple theorems on probability, Independence of events, Bayes Theorem, Discrete and continuous random variables, Binomial, Poisson and Normal distributions; Expectation and moments, Independence of random variables, Chebyshev's inequality
4 Linear Programming Basic Concepts : Convex sets, Linear Programming Problem (LPP). Examples of LPP. Hyperplane, open and closed Half-spaces. Feasible, basic feasible and optimal solutions. Extreme point and graphical method.
5 Real Analysis : Finite, countable and uncountable sets, Bounded and unbounded sets, Archimedean property, ordered field, completeness of R, Extended real number system, limsup and liminf of a sequence, the epsilon-delta definition of continuty and convergence, the algebra of continuous functions, monotonic functions, types of discontinuties, infinite limits and limits at infinity, functions of bounded variation. elements of metric spaces.
6 Complex Analysis : Riemann Sphere and Stereographic projection. Lines, circles, crossratio. Mobius transformations, Analytic functions, Cauchy-Riemann equations, line integrals, Cauchy's theorem, Morera's theorem, Liouville's theorem, integral formula, zero-sets of analytic functions, exponential, sine and cosine functions, Power siries representation, Classification of singularities, Conformal mapping.
7 Algebra : Group, subgroups, Normal subgroups, Quotient Groups, Homomorphisms, Cyclic Groups, Permutation Groups, Cayley's Theorm, Rings, Ideals, Integral Domains, Fields, Polynomial Rings.
8 Linear Algebra : Vector spaces, subspaces, quotient spaces, Linear indepenence, Bases, Dimension. The algebra of linear Transformations, kernal, range, isomorphism, Matrix Representation of a linear transormation, change of bases, Linear functionals, dual space, projection, determinant function, eigenvalues and eigen vectorsCayley-Hamilton Theorem,Invariant Sub-spaces, Canonical Forms : diagonal form, Triangular form, Jordan Form. Inner product spaces.
9 Differential Equations : First order ODE, singular solutions initial value Problems of First Order ODE, General theory of homogeneous and non-homogeneous Linear ODE, Variation of Paraneters. Lagrange's and Charpit's methods of solving First order Partial Differental Equations. PDE's of higher order with constant coefficients
10 Data Analysis Basic Concepts : Graphical representation, measures of central tendency and dispersion. Bivariate data correlation and regression. Least squares-polynomial regression, Applications of normal distribution.
11 Probability : Axiomatic definition of probability. Random variables and distribution functions (univariate and multivariate); expectation and moments; independent events and independent random variables; Bayes theorem; marginal and conditional distribution in the multivariate case, covariance matrix and correlation coefficients (product moment, partial and multipal), regression. Moment generating functions, characteristic functions; probability inequalities (Tehebyshef, Markov, Jensen). Convergence in probability and in distribution; weak law of large numbers and central limit theorem for independent indentically distributed random variables with finite variance.
12 Probability Distribution : Bemoulli, Binomial, Multinomial. Hypergeomatric, Poisson, Geometric and Negative binomial distributions, Uniform, exponential, Cauchy, Beta, Gamma, and normal (univariate and multivariate) distributions Transformations of random variables; sampling distributions. t, F and chi-square distributions as sampling distributions, as sampling distributions, Standard errors and large sample distributions. Distribution of order statistics and range.
13 Theory of Statistics : Methods of estimation : maximum likelihood method, method of moments, minimum chi-square method, least- squares method. Unbiasedness, efficiencey, consistency. Cramer-Rao inequality. Sufficient, Statistics. Rao-Blackwell theorem. Uniformly minimum variance unbiased estimators. Estimation by confidence intervals. Tests of hypotheses : Simple and composite hypotheses, two types of errors, critical region, randomized test, power function, most powerful and uniformly most powerful tests. Likelihood-ratio tests. Wald's sequential probability ratio test.
14 Statistical Methods and Data Analysis : Tests for mean and variance in the normal distribution : one-population and two-population cases; related confidence intervals. Tests for product moment, partial and multiple correlation coefficients; comparison of k linear regressions. Fitting polynomial regression; related test Analysis of discrete date: chi-square test of goodness of fit, contingency tables. Analysis of variance : one-way and two-way classification (equal number of observations per cell). Large sample tests through normal approximation. Nonparametric tests : sign test, Median test, Mann-Whitney test, Wilcoxon test for one and two-samples, rank correlation and test of independence.
15 Operational Research Modelling : Definition and scope of Operational Research. Different types of models. Replacement models and sequencing theory, Inventory problems and their analytical structure. Simple deterministic and stochastic models of inventory control. Basic characteristics of queueing system, different performance measures, steady state solution of Markovian queueing models: M/M/1, M/M/1 with limited waiting space M/M/C, M/M/C with limited waiting space.
16 Linear Programming : Linear Programming, Simplex method, Duality in linear programming. Transformation and assignment problems. Two person-zero sum games. Equivalence of rectangular game and linear programming.
17 Finite Population : Sampling Techniques and Estimation: Simple random sampling with and without replacement. Stratified sampling; allocation problem; systematic sampling Two stage sampling. Related estimation problems in the above cases.
18 Design of Experiments : Basic principles of experimental design. Randomisation structure and analysis of completely randomised, randomised blocks and Latin-square designs. Factorial experiments. Analysis of 2n factorial experiments in randomised blocks.
S. No PAPER - III
1 Real Analysis : Riemann integrable functions; improper integrals, their convergence and uniform convergence. Eulidean space R", Bolzano-Weierstrass theorem, compact Subsets of R", Heine-Borel T\theorem, Fourier series. Continuity of functions on R", Differentiability of F:R"-Rm. Properties of differential, partial and directional derivatives, continuously differentiable functions. Taylor's series. Inverse function theorem, Implieit function theorem. Integral functions, line and surface integrals, Green's theorem, Stoke's theorem.
2 Complex Analysis : Cauchy's theorem for convex regions. Power series representation of Analtic functions. Liouville's theorem, Fundamental theorem of algebra Riemann's theorem on removable singularities, maximum modulus principle. Schwarz Iemma, Open Mapping theorem, Casorattl-Weierstrass-theorem, Weierstrass's theorem on uniform convergence on compact sets, Bilinear transformations, Multivalued Analytic Functions, Riemann Surfaces.
3 Algebra : Symmetric groups, Alternating groups, Simple groups, Rings, Maximal Ideals, Prime Ideals, Integral domains Euclidean domains, principal Ideal domains, Unique Factorisation domains, quotient fileds, Finite fields, Algebra of Linear Transformations, Reduction of matrices to Canonical Forms, Inner Product Spaces, Orthogonality, Quadratic Forms, Reduction of quadratic forms.
4 Advanced Analysis : Elements of Metric Spaces, Convergence, continuity, compactness, Connectedness, Weierstrass's approximation Theorem, Completeness, Bare category theorem, Labesgue measure, Labesgue Integral, Differentiation and Integration.
5 Advanced Algebra : Conjugate elements and class equations of finite groups, Sylow theorems, solvable groups, Jordan Holder Theorem, Direct Products, Structure Theorem for finite abelian groups, Chain conditions on Rings; Characteristic of Field, Field extensions, Elements of Galois theory, solvability by Raducals, Ruler and compass construction.
6 Functional Analysis : Banach Spaces Hahn-Banach Theorem, Open mapping and closed Graph Theorems. Principal of Uniform boundedness, Boundedness and continuity of Linear Transformations, Dual Space, Embedding in the second dual, Hilbert Spaces, Projections. Orthonormal Basis, Riesz-representation theorem, Bessel's Inequality, parsaval's identity, self adjoined operators, Normal Operators.
7 Topology : Elements of Topological Spaces, Continuity, convergence, Homeomorphism, Compactness, Connectedness, Separation Axioms, First and Second Countability, Separability, Subspaces, Product Spaces, quotient spaces. Tychonoft's Theorem, Urysohn's Metrization theorem, Homotopy and Fundamental Group.
8 Discrete Mathematics : Partially ordered sets, Lattices, Cornplete Lattices, Distrbutive lattices, Complements, Boolean Algebra, Boolean Expressions, Application to switching circuits, Elements of Graph Theory, Eulerian and Hamiltonian graphs, planar Graphs, Directed Graphs, Trees, Permutations and Combinations, Pigeonhole principle, principle of Inclusion and Exclusion, Derangements.
9 Ordinary and partial Differential Equations : Existence and Uniqueness of solution dy/dx = f (x,y) Green's function, sturm Liouville Boundary Value Problems, Cauchy Problems and Characteristics, Classification of Second Order PDE, Separation of Variables for heat equation, wave equation and Laplace equation, Special functions.
10 Number Theory : Divisibility; Linear diophantine equations. Congruences. Quadratic residues; Sums of two squares, Arithmatic functions Mu, Tau, and Signa (and ).
11 Machanics : Generalise coordinates; Lagranges equation; Hamilton's cononical equations; Variational Principles-Hamilton's pronciples and plrinciples of least action; Two dimensional motion of rigid bodies; Euler's dynamical equations for the motion of rigid body; Motion of a rigid body about an axis; Motion about revolving axes.
12 Elasticity : Analysis of strain and stress, strain and stress tensors; Geometrical representation; Compatibility conditions; Strain energy function; Constritutive relations; Elastic solids "Hookes law; Saint-Venant"s principle, Equations of equilibrium; Plane problem-Airy's stress function vibrations of elastic, cylindrical and spherical media.
13 . Fluid Mechanics : Equation of continuity in fluid motion; Euler's equations of motion for perfect fluids; Two dimensional motion complex potential; Motion of sphere in perfect liquid and montion of liquid past a sphere; vorticity; Navier-Stokes's equations for viscous flowssome exact solutions.
14 Differetial Geometry : Space curves-their curvature and torsion; Serret Frehat Formula; Fundamental theorem of space curves; Curves on sirfaces; First and second fundamental form; Gaussian curvatures; Principal directions and principal curvatures; Goedesics, Fundamental equations of surface theory.
15 Calculus of Variations : Linear functionals, minimal functional theorem, general variation of a functional, Euler-Lagrange equation; Variational methods of boundary value problems in ordinary and partial differential equations.
16 Linear Integral Equations : Linear Integral Equations of the first and second kind of Fredholm and Volterra type; solution by successive substitutions and successive approximations; Solution of equations with separable kernels; The Fredholm Alternative; Holbert-Schmidt theory for symmetric kernels.
17 . Numerical analysis : Finite differences, Interpolation; Numerical solution of algebric equation; Iteration; Newton-Raphason Method; Solution on Linear system; Direct method; Gauss elminaiton method; Matrix-Inversion eigenvalue problems; Numerical differentiation and integration. Numerical solution of ordinary differential equation; iteration method, Picard's method , Euler's method and improved Euler's method.
18 Integral Transform : Laplace transform; Transform of elementary functions, Transform of Derivatives, Inverse Transform, Convolution Theorem, Applications, Ordinary and Partial differential equations; Fourier transform; sine and cosine transform, Inverse Fourier Transform, Application to ordinary and partial differential equations.
19 Mathematical Programming : Revised simplex method, Dual simplex method, Sensitivity analysis and parametric linear programming. Kuhn-Tucker conditions of optimality. Quadratic programming; methods due to Beale, Wofle and Vandepanne, Duality in quadratic programmming, self duality, Integer programming.
20 Measure Theory : Measurable and measure spaces : Extension of measures,signed measures, Jordan-Hahn decomposition theorems. Integratiuon, monotone convergence theorem, Fatou's lemma, dominaated convergence theorem. Absolute continuity, Radon Nikodym theorem, Product measures, Fubini's theorem.
21 Probability : Sequences of events and random variables: Zero-one laws of Borel and Kolmogorov. Almost sure convergence, convergence in mean square, Khintchine's weak law of large numbers; Kolmogorov's inequality, strong law of large numbers. Convergence of series of random variables, three-series criterion. Central limit theorems of Liapounov and Lindeberg-Feller. Conditional expectation, martingales.
22 Distribution Theory : Properties of distribution functions and characteristic functions; continuty theorem, inversion formula, Representation of distribution function as a mixture of discrete and continuous distribution functions; Convolutions, marginal and conditional distributions of bivariate discrete and continuous distributions. Relations between characteristic functions and moments; Moment inequalities of Holder and Minkowski.
23 Statistical Inference and Decision Theory : Statistical decision problem : non-randomized, mixed and randomized decision rules; risk function admissibility, Bayes rules, minimax rules, least favourable distributions, complete class and minimal complete class. Decision problem for finite parameter space. Convex loss function. Role of sufficiency. Admissible, Bayes and minimax estimators; illustrations. Unbiasedness. UMVU estimators. Families of distributons with monotone likelihood property, exponential family of distributions. Test of a simple hypothesis against a simple alternative from decision-theoretic viewpoint. Tests with Neyman structure. Uniformly most powerful unbiased tests. Locally most powerful tests. Inference on location and scale parameters; estimation and tests. Equivariant estimators. Invariance in hypothesis testing
24 Large sample statistical methods : Various modes of convergence. Op and op, CLT, Sheffe's theorem, Polya's theorem and Slutsky's theorem. Transformation and variance stabilizing formula. Asymptotic disribution of function of sample moments. Sample quantiles. Order statistics and their functions. Tests on correlations, coefficient of variation, skewness and kurtosis. Pearson Chi-square, contingency Chi-square and likelihood ratio statistics. U-statistics consistency of Tests. Asymptotic relative efficiency.
25 Multivariate Statistical Analysis : Singular and non-singular multivariate distributions. Characteristics functions. Multivariate normal distributions, margrinal and conditional distributions; distribution of linear forms, and quadratic forms, Cochran's theorem. Inference on parameters of multivariate normal distributions, one-population and two population cases. wishart distribution. Hotellings T2, Mahalanobis D2 Discrimination analysis, Principal components, Canonical correlations, Cluster analysis.
26 Linear Models and Regression : Standard Gauss-Markov models; Estimability of parameters; best linear unbiased extimates(BLUE); Method of least squares and Gauss-Markovtheorem; Variance-covariance matrix of BLUES. Tests of linear hypothesis; One-way and two-way classifications. Fixed, random and mixed effects models (two-way classifications only); variance components, Bivariate and multiple linear regression; Polynomial regression; use of ortheogonal polynomials. Analysis of covarance. Linear and nonlinear regression outliers.
27 Sample Surveys : Sampling with varying probability of selection, Hurwitz-Thompson estimator; PPS sampling: Double sampling. Cluser sampling. Non-sampling errors: Interpentrating samples. Multiphase sampling. Ratio and regession methods of estimation.
28 Design of Experiments : Factorial experiments, confounding and fractional replication. Split and strip plot designs; Quasi-Latin square designs; Youden square. Design for study of response surfaces; first and second order designs. Incomplete block designs; Balanced, connectedness and orthogonality, BIBD with recovery of inter-block information PBIBD with 2 associate classes. Analysis of series of experiments, esimation of residual effects. Construction of orthogonal-Latin squares, BIB designs, and confounded factorial designs. Optimality criteria for experimental designs.
29 Time-Series Analysis : Discrete-parameter stochastic processes; strong and weak stationarity; autocovariance and autocorrelation. Moving average, autoregressive, autoregressive moving average and autoregressive intgegfrated moving average processes. Box-Jenkins models. Estimation of the parameters in ARIMA models; forecasting. Periodogram and correlogram analysis
30 Stochastic Proceses : Markov chains with finite and countable state space, classification of states, limiting behaviour of n-step transition probabilities, stationary distribution; branching processes; Random walk; Gambler's ruin. Markov processes in continuous time; Poisson processes, birth and death processes, Wiener process.
31 Demography and Vital Statistics : Measures of fertility and mortality, period and Cohort measures. Life tables and its applications; Methods of construction of abridged life tables. Application of stable population theory to estimate vital rates. Popultion projetions. Stochastic models of fertility and reproduction.
32 Industrial Statistics : Control charts for variables and attributes; Acceptance sampling by attribites; single, double and sequential sampling plans; OC and ASN functions, AOQL and ATI; Acceptance sampling by varieties. Tolerance limits Reliability analysis: Hazard function, distribution with DFR and IFR; Series and parallel systems. Life testing experiments.
33 Inventory and Queueing theory : Inventory (S,s) policy periodic review models with stochastic demand. Dynamic inventory models. Probabilistic re-order point, lot size inventory system with and without lead time. Distribution free analysis. Solution of inventory problem with unknown density function. Warehousing problem. Queues: Imbedded markov chain method to obtain steady state solution of M/G/1, G/M/1 and M/D/C, Network models. Machine maintenance models. Design and control of queueing systems.
34 Dynamic Programming and Marketing : Nature of dynamic programming, Deterministic processes, Non-sequential discrete optimisation-allocation problems, assortment problems. Sequential discrete optimisation long-term planning problems, multi stage production processes. Functional approximations. Marketing systems, application of dynamic programming to marketing problems. Introduction of new product, objective in setting market price and its policies, purchasing under Fluctuating prices, Advertising and promotional decisions, Brands swiching analysis, Distribution decisions
S. No UNIT - 1
1 Analysis: Elementary set theory, finite, countable and uncountable sets, Real number system as a complete ordered field, Archimedean property, supremum, infimum. Sequences and series, convergence, limsup, liminf. Bolzano Weierstrass theorem, Heine Borel theorem. Continuity, uniform continuity, differentiability, mean value theorem. Sequences and series of functions, uniform convergence. Riemann sums and Riemann integral, Improper Integrals. Monotonic functions, types of discontinuity, functions of bounded variation, Lebesgue measure, Lebesgue integral. Functions of several variables, directional derivative, partial derivative, derivative as a linear transformation, inverse and implicit function theorems Metric spaces, compactness, connectedness. Normed linear Spaces. Spaces of continuous functions as examples.on
2 Linear Algebra: Vector spaces, subspaces, linear dependence, basis, dimension, algebra of linear transformations. Algebra of matrices, rank and determinant of matrices, linear equations. Eigenvalues and eigenvectors, Cayley-Hamilton theorem. Matrix representation of linear transformations. Change of basis, canonical forms, diagonal forms, triangular forms, Jordan forms. Inner product spaces, orthonormal basis
S. No UNIT - 2
1 Complex Analysis: Algebra of complex numbers, the complex plane, polynomials, power series, transcendental functions such as exponential, trigonometric and hyperbolic functions. Analytic functions, Cauchy-Riemann equations. Contour integral, Cauchy's theorem, Cauchy's integral formula, Liouville's theorem, Maximum modulus principle, Schwarz lemma, Open mapping theorem. Taylor series, Laurent series, calculus of residues. Conformal mappings, Mobius transformations.
2 Algebra: Permutations, combinations, pigeon-hole principle, inclusion-exclusion principle, derangements. Fundamental theorem of arithmetic, divisibility in Z, congruences, Chinese Remainder Theorem, Euler's - function, primitive roots. Groups, subgroups, normal subgroups, quotient groups, homomorphisms, cyclic groups, permutation groups, Cayley's theorem, class equations, Sylow theorems. Rings, ideals, prime and maximal ideals, quotient rings, unique factorization domain, principal ideal domain, Euclidean domain. Polynomial rings and irreducibility criteria. Fields, finite fields, field extensions, Galois Theory
3 Topology: basis, dense sets, subspace and product topology, separation axioms, connectedness and compactness.
S. No UNIT - 3
1 Ordinary Differential Equations (ODEs): Existence and uniqueness of solutions of initial value problems for first order ordinary differential equations, singular solutions of first order ODEs, system of first order ODEs. General theory of homogenous and non-homogeneous linear ODEs, variation of parameters, Sturm-Liouville boundary value problem, Green's function.
2 Partial Differential Equations (PDEs): Lagrange and Charpit methods for solving first order PDEs, Cauchy problem for first order PDEs. Classification of second order PDEs, General solution of higher order PDEs with constant coefficients, Method of separation of variables for Laplace, Heat and Wave equations
3 Numerical Analysis : Numerical solutions of algebraic equations, Method of iteration and Newton-Raphson method, Rate of convergence, Solution of systems of linear algebraic equations using Gauss elimination and Gauss-Seidel methods, Finite differences, Lagrange, Hermite and spline interpolation, Numerical differentiation and integration, Numerical solutions of ODEs using Picard, Euler, modified Euler and Runge-Kutta methods.
4 Calculus of Variations: Variation of a functional, Euler-Lagrange equation, Necessary and sufficient conditions for extrema. Variational methods for boundary value problems in ordinary and partial differential equations.
5 Linear Integral Equations: Linear integral equation of the first and second kind of Fredholm and Volterra type, Solutions with separable kernels. Characteristic numbers and eigenfunctions, resolvent kernel.
6 Classical Mechanics: Generalized coordinates, Lagrange's equations, Hamilton's canonical equations, Hamilton's principle and principle of least action, Two-dimensional motion of rigid theory of small oscillations.
S. No UNIT - 4
1 Descriptive statistics, exploratory data analysis Sample space, discrete probability, independent events, Bayes theorem. Random variables and distribution functions (univariate and multivariate); expectation and moments. Independent random variables, marginal and conditional distributions. Characteristic functions. Probability inequalities (Tchebyshef, Markov, Jensen). Modes of convergence, weak and strong laws of large numbers, Central Limit theorems (i.i.d. case). Markov chains with finite and countable state space, classification of states, limiting behaviour of n-step transition probabilities, stationary distribution, Poisson and birth-and-death processes. Standard discrete and continuous univariate distributions. sampling distributions, standard errors and asymptotic distributions, distribution of order statistics and range.
2 Methods of estimation, properties of estimators, confidence intervals. Tests of hypotheses: most powerful and uniformly most powerful tests, likelihood ratio tests. Analysis of discrete data and chi-square test of goodness of fit. Large sample tests. Simple nonparametric tests for one and two sample problems, rank correlation and test for independence. Elementary Bayesian inference. Gauss-Markov models, estimability of parameters, best linear unbiased estimators, confidence intervals, tests for linear hypotheses. Analysis of variance and covariance. Fixed, random and mixed effects models. Simple and multiple linear regression. Elementary regression diagnostics. Logistic regression. Multivariate normal distribution, Wishart distribution and their properties. Distribution of quadratic forms. Inference for parameters, partial and multiple correlation coefficients and related tests. Data reduction techniques: Principle component analysis, Discriminant analysis, Cluster analysis, Canonical correlation. Simple random sampling, stratified sampling and systematic sampling. Probability proportional to size sampling. Ratio and regression methods. Completely randomized designs, randomized block designs and Latin-square designs. Connectedness and orthogonality of block designs, BIBD. 2K factorial experiments: confounding and construction. Hazard function and failure rates, censoring and life testing, series and parallel systems. Linear programming problem, simplex methods, duality. Elementary queuing and inventory models. Steady-state solutions of Markovian queuing models: M/M/1, M/M/1 with limited waiting space, M/M/C, M/M/C with limited waiting space, M/G/1.
3 All students are expected to answer questions from Unit I. Students in mathematics are expected to answer additional question from Unit II and III. Students with in statistics are expected to answer additional question from Unit IV
S. No UNIT - 1
1 Analysis:> Elementary set theory, finite, countable and uncountable sets, Real number system as a complete ordered field. Archimedean property, supremum, infimum. Sequences and series, convergence, limsup, liminf. Bolzano Weierstrass theorem, Heine Borel theorem Continuity, uniform continuity, differentiability, mean value theorem. Sequences and series of functions, uniform convergence. Riemann sums and Riemann integral, Improper Integrals. Monotonic functions, types of discontinuity, functions of bounded variation, Lebesgue measure,Lebesgue integral. Functions of several variables, directional derivative, partial derivative, derivative as a linear transformation, inverse and implicit function theorems.Metric spaces, compactness, connectedness. Normed linear Spaces. Spaces of continuous functions as examples.
2 Linear Algebra :Vector spaces, subspaces, linear dependence, basis, dimension, algebra of linear transformations.Algebra of matrices, rank and determinant of matrices, linear equations.Eigenvalues and eigenvectors, Cayley-Hamilton theorem. Matrix representation of linear transformations. Change of basis, canonical forms, diagonal forms. triangular forms, Jordan forms.Inner product spaces, orthonormal basis. Quadratic forms, reduction and classification of quadratic forms.
S. No UNIT - 2
1 Complex Analysis: Algebra of complex numbers, the complex plane, polynomials, power series, transcendental functions such as exponential, trigonometric and hyperbolic functions. Analytic functions, Cauchy-Riemann equations.Contour integral, Cauchy's theorem, Cauchy's integral formula, Liouville's theorem, Maximum modulus principle, Schwarz lemma, Open mapping theorem.Taylor series, Laurent series, calculus of residues. Conformal mappings, Mobius transformations.
2 Algebra:Permutations, combinations, pigeon-hole principle, inclusion-exclusion principle. derangements.Fundamental theorem of arithmetic, divisibility in Z. congruences, Chinese Remainder Theorem, Euler's O-function, primitive roots.groups, Cayley's theorem, class equations, Sylow theorems. Groups, subgroups, normal subgroups, quotient groups, homomorphisms, cyclic groups, permutation domain, Euclidean domain.Rings, ideals, prime and maximal ideals, quotient rings, unique factorization domain, principal ideal Polynomial rings and irreducibility criteria. Fields, finite fields, field extensions, Galois Theory.
3 Topology: basis, dense sets, subspace and product topology, separation axioms, connectedness and compactness,
S. No UNIT - 3
1 Ordinary Differential Equations (ODES): Existence and uniqueness of solutions of initial value problems for first order ordinary differential equations, singular solutions of first order ODEs, system of first order ODES. General theory of homogenous and non-homogeneous linear ODES, variation of parameters, Sturm-Liouville boundary value problem, Green's function.
2 Partial Differential Equations (PDES):Lagrange and Charpit methods for solving first order PDEs, Cauchy problem for first order PDES. Classification of second order PDEs, General solution of higher order PDEs with constant coefficients, Method of separation of variables for Laplace, Heat and Wave equations.
3 Numerical Analysis:Numerical solutions of algebraic equations, Method of iteration and Newton-Raphson method, Rate of convergence. Solution of systems of linear algebraic equations using Gauss elimination and Gauss-Seidel methods, Finite differences, Lagrange, Hermite and spline interpolation, Numerical differentiation and integration, Numerical solutions of ODEs using Picard, Euler, modified Euler and Runge-Kutta methods.
4 Calculus of Variations:Variation of a functional, Euler-Lagrange equation, Necessary and sufficient conditions for extrema. Variational methods for boundary value problems in ordinary and partial differential equations.
5 Linear Integral Equations:Linear integral equation of the first and second kind of Fredholm and Volterra type, Solutions with separable kernels. Characteristic numbers and eigenfunctions, resolvent kemel.
6 Classical Mechanics:Generalized coordinates, Lagrange's equations, Hamilton's canonical equations, Hamilton's principle and principle of least action, Two-dimensional motion of rigid bodies, Euler's dynamical equations for the motion of a rigid body about an axis, theory of small oscillations.
S. No UNIT - 4
1 Descriptive statistics, exploratory data analysis Sample space, discrete probability, independent events, Bayes theorem. Random variables and distribution functions (univariate and multivariate), expectation and moments. Independent random variables, marginal and conditional distributions. Characteristic functions. Probability inequalities (Tchebyshef, Markov, Jensen). Modes of convergence, weak and strong laws of large numbers, Central Limit theorems (i.i.d. case).
Markov chains with finite and countable state space, classification of states, limiting behaviour of n-step transition probabilities, stationary distribution, Poisson and birth-and-death processes.
Standard discrete and continuous univariate distributions, sampling distributions, standard errors and asymptotic distributions, distribution of order statistics and range.
Methods of estimation, properties of estimators, confidence intervals. Tests of hypotheses: most powerful and uniformly most powerful tests, likelihood ratio tests. Analysis of discrete data and chi-square test of goodness of fit. Large sample tests.
Simple nonparametric tests for one and two sample problems, rank correlation and test for independence. Elementary Bayesian inference.
Gauss-Markov models, estimability of parameters, best linear unbiased estimators, confidence intervals,tests for linear hypotheses. Analysis of variance and covariance. Fixed, random and mixed effects models. Simple and multiple linear regression. Elementary regression diagnostics. Logistic regression.
Multivariate normal distribution. Wishart distribution and their properties. Distribution of quadratic forms. Inference for parameters, partial and multiple correlation coefficients and related tests. Data reduction techniques: Principle component analysis. Discriminant analysis, Cluster analysis, Canonical correlation.
Simple random sampling, stratified sampling and systematic sampling. Probability proportional to size sampling. Ratio and regression methods.
Completely randomized designs, randomized block designs and Latin-square designs. Connectedness and orthogonality of block designs, BIBD. 2k factorial experiments: confounding and construction.
Hazard function and failure rates, censoring and life testing, series and parallel systems.
Linear programming problem, simplex methods, duality. Elementary queuing and inventory models. Steady-state solutions of Markovian queuing models: M/M/1, M/M/1 with limited waiting space, M/M/C. M/M/C with limited waiting space, M/G/1.

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