M.Sc (Statistics)
This is a four semester master level programme with an intake of 15 students. Apart from teaching the core Statistics subjects, the students are also trained to handle real life problems through the practical classes. As a part of the course they are taught some programming languages and also exposed to various Statistical softwares such as SPSS, Mathlab and SAS.
Eligibility: B.Sc. degree in Mathematics or Statistics main with at least 55% marks for optional subjects taken together.
Course Structure
M.Tech (Engineering Statistics)
The objective of this programme is to teach statistical methods to engineers so as to equip them to apply the recent statistical tools in the industrial sector. There is wide scope for this course as students are trained in statistical methods like reliability engineering, experimental design, statistical process control and ISO 9000, operation research, forecasting, software quality and reliability, six sigma tools and SAS programming, which are essential to assess and improve the quality and productivity in industrial sector. This course is aimed at bridging the gap between theoretically trained statisticians and the professional engineers. The first two semesters are devoted to classroom teaching and laboratory experiments. In the third and fourth semesters, the candidates will be sent to undertake a project work in industries of their choice. Graduates of this course are well placed in industries, software/BPO companies and academic/research organizations.
Eligibility: B.Tech or equivalent degree or AMIE in any discipline with a first class (60%) from any recognised university or institution with valid GATE score.
Course Structure
Ph.D (Statistics)
The Department offers supervision for research degrees of Ph.D in several branches of statistics. The thrust areas include both theoretical and applied. The research scholars get financial support from the funding agencies such as University Grants Commission (UGC), Council of Scientific and Industrial Research (CSIR) and National Board for Higher Mathematics (NBHM). The University also offers a limited number of Scholarships for eligible candidates.
Thrust Areas of Research
 |
Distribution Theory |
|
Reliability Theory |
|
Time Series Analysis |
|
Stochastic Processes |
|
Survival Analysis |
|
Demography |
|
Population Studies |
|
Chaos and Nonlinear Time Series |
|
TQM & ISO 9000 |
|
Design of Experiments |
|
Industrial Statistics |
Course Structure - M.Sc Statistics
Semester I
Course Code |
Paper |
C/E |
Credits |
| STA2101 |
Mathematical methods for Statistics |
C |
4 |
STA2102 |
Probability Theory |
C |
4 |
| STA2103 |
Probability Distributions |
C |
4 |
| STA2104 |
Sampling Theory |
C |
4 |
| STA2105 |
Elective I |
E |
4 |
Semester II
Course Code |
Paper |
C/E |
Credits |
| STA2201 |
Statistical Inference 1 |
C |
4 |
STA2202 |
Probability Theory II |
C |
4 |
| STA2203 |
Stochastic Processes |
C |
4 |
| STA2204 |
Practical I using SPSS |
C |
2 |
| STA2205 |
Elective II |
E |
4 |
Semester III
Course Code |
Paper |
C/E |
Credits |
| STA2301 |
Statistical Inference II |
C |
4 |
STA2302 |
Multivariate Analysis |
C |
4 |
| STA2303 |
Applied Regression Analysis |
C |
4 |
| STA2304 |
Practicals II using Mathlab |
C |
2 |
| STA2305 |
Elective III |
E |
4 |
Semester IV
Course Code |
Paper |
C/E |
Credits |
| STA2401 |
Design and Analysis of Experiments |
C |
4 |
STA2402 |
Statistical Quality Assuarance |
C |
4 |
| STA2403 |
Practicals III using SAS and comprehensive viva voce |
C |
4 |
| STA24041 |
Elective IV |
C |
2 |
| STA2405 |
Elective V |
E |
4 |
List of Electives:
1 |
Acturial Statistics |
2 |
Advanced Distribution Theory |
3 |
Advanced Probability Theory |
4 |
Advanced Stochastic Processes |
5 |
Applied Statistics |
6 |
Bayesian Inference and Decision |
7 |
Demographic Techniques |
8 |
Directional Data Analysis |
9 |
Inference for Stochastic Processes |
10 |
Multivariate Methods |
11 |
Operations Research |
12 |
Reliability Modelling and Analysis |
13 |
Statistical Computing |
14 |
Statistical forecasting |
15 |
Statistical Genetics |
16 |
Survival Analysis |
17 |
Time Series Analysis |
Course Structure - M.Tech Engineering Statistics - Syllabus
Semester I
Course Code |
Paper |
C/E |
Credits |
STA3101 |
Basic Statistics |
C |
4 |
| STA3102 |
Reliability and life testing |
C |
4 |
| STA3103 |
Practical |
C |
2 |
| STA3104 |
Seminar and Viva |
C |
- |
| STA3105 |
Simulation Modelling and Analysis |
E |
4 |
| STA3106 |
Statistical Methods for Quality Assurance |
E |
4 |
| STA3107 |
Total Quality Management |
E |
4 |
| STA3108 |
Operations Research |
E |
4 |
| STA3109 |
Management and Maintenance of information systems |
E |
4 |
| STA3110 |
Production Planning and Control |
E |
4 |
| STA3111 |
Manufacturing Processes and measurements for Quality |
E |
4 |
Semester II
Course Code |
Paper |
C/E |
Credits |
| STA3201 |
Industrial Experimental Design |
C |
4 |
STA3202 |
Forecasting and Design |
C |
4 |
| STA3203 |
Practical-2 |
C |
2 |
| STA3204 |
Seminar and Viva |
C |
- |
| STA3205 |
Methods Engineering |
E |
4 |
| STA3206 |
Engineering Maintainability |
E |
4 |
| STA3207 |
E-commerce |
E |
4 |
| STA3208 |
Software Quality Management |
E |
4 |
| STA3209 |
Multivariate Methods |
E |
4 |
| STA3210 |
Statistical Inference |
E |
4 |
Semester III
Course Code |
Paper |
C/E |
Credits |
| STA 3301 |
Project Progress Evaluation |
C |
18 |
Semester IV
Course Code |
Paper |
C/E |
Credits |
| STA 3401 |
Project Dissertion Evaluation and Viva-Voce |
C |
18 |
|
