Syllabus: Estimation : Unbiased ness, consistency, sufficiency, efficiency, factorisation theorem, completeness. Rao-Blackwell theorem, Lehmann-Scheffe theorem, Basu's theorem, Cramer-Rao lower bounds. Methods of estimation : methods of moments, maximum likelihood method, maximum Chi-squared method, least square method. Asymptotic distribution of maximum likelihood estimates. Interval Estimation : pivotal method, general method. Optimum Estimation Procedures : Loss, risk, unbiased ness, Bayes, Minimax, Invariance (location, scale, location – scale)

Syllabus: Linear regression, Multiple Linear regression Polynomial regression, Collinearity, Variable selection, Diagnostics, Weighted least squares, Nonleast squares estimation, Linear models.

Evaluation Criteria: End-of-semester examination and assignments

Syllabus: Principles of design, replication and randomization, Completely randomized design, Concept of blocking, Randomized complete block design, Latin square design, effect of assumption failure in ANOVA and transformation, Factorial experiments, Principle of confounding, Fractional Replications, Analysis of confounded experiments, Cross-over designs, split -plot designs, Split-split plot designs, Incomplete block designs, Idea of covariance, Analysis of covariance, Use of Statistical packages for analysis of experiments.

Syllabus: Survey Methods : Main steps in planning and execution of large surveys, Sampling & non – sampling errors. Basic concepts of sampling, Simple Random Sampling, Theory involved in estimation procedures, Estimation using Ratio and Regression methods. Stratified Random Sampling. Proportional and optimum allocation. Cluster sampling with equal and unequal probabilities. Systematic sampling : Multi-stage sampling, Design effect and intra-cluster correlation. Complex surveys and related problems, Sample size determination, Sources of errors in surveys.

Evaluation Criteria: Examinations and assignments

Syllabus: This course is offered by the Department of Mathematics

Syllabus: Introduction to statistical packages - SPSS, GLIM, SAS, INSTAT. Case studies would consist of at least 9 continuously assessed individual practical exercises and one group project. The emphasis will be on applications of theory covered in the other subject areas as well as on presentation and report writing.

Evaluation Criteria: 20% for group project 80% for individual case studies

Syllabus: Basic designs for epidemiological studies, relative risk and odds ratio, confounding and interaction. Analysis of data from cohort and case-control studies. Matched case control studies. Clinical trials; protocols for clinical trials, cross-over designs, allocation to treatment, sample size determination, phase I and phase II studies. Analysis of survival data; the survival and hazard functions, non-parametric procedures : Kaplan Meier estimate of survivor functions, log rank test for comparing two groups of survival times. Parametric modeling : proportional hazards model, Cox's proportional hazards model.

Syllabus: PART A - Operational Research Introduction : Purpose of modeling and types of modeling, Linear programming models, model building,. Use of different algorithms, different types of problems. Duality, theorems, shadow prices. Sensitivity analysis. Transportation models and their solutions. Integer programming. Project planning and control. Inventory control models. Queuing models. PART B - Quality Control Sampling plans of attribute type; Sampling plans based on Binomial, Hyper geometric and Poisson distributions. Dodge and Romig approach, Decision theory approach. Sampling inspection by variables, Double sampling plans, Continuous sampling plans, Tolerance intervals, Control charts.

Syllabus: Please see under General Degree courses offered by this department

Dependencies: None

Syllabus: Sets and relations ; set operations, equivalence relation, partial order, order. Vectors and Matrices; Rank, Range, Nullspace, Linear equations. Vector spaces - subspaces, basis and dimension.Linear transformation, change of basis. Inner products ; Orthogonality, Orthogonalization process.

Evaluation Criteria: Examinations and assignments

Dependencies: None

Syllabus: Concept of Management and evolution of Management thoughts; the scientific management movement and other schools of thoughts that followed. Socio-industrial imperatives for evolution of thoughts. Functional areas of management: planning, organizing, staffing, monitoring and evaluation. Selected new developments in modern management practices.

Evaluation Criteria: End-of-semester examination (80%), Continuous assessments (20%)

Suggested Readings: Robbins and DeCenzo, “Fundamentals of Management”, 8h Edition, 1998, Prentice Hall. Donnelley, Gibson and Ivancevich Irwi, “Fundamentals of Management”, 10th Edition, 1998.

Dependencies: None

Syllabus: Formulation of linear programming problems, Solving 2 variable LP problems using the graphical method. The Simplex algorithm. The Simplex method in matrix notation. The degeneracy and convergence of the Simplex algorithm. Sensitivity and parametric analyses. The Dual Simplex method, Big M method and the Two phase Simplex method.

Evaluation Criteria: Examinations