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M.Sc. Statistics

Statistics is the new technology for development planning and research in all sciences including social and management sciences. These are part and parcel for all disciplines of scientific and systematic study. Indian Statistical Services is specially established for coordinating all statistical activities in the national and state levels. UPSC conducts examinations for recruiting ISS officers  and our students will get opportunities at national level as officers for the conduct of national sample surveys and formulating national policies for growth and development of our nation. The Reserve Bank of India and the Ministry of Agriculture, Ministry of Commerce and Industry, Ministry of Health and Family Welfare etc have special statistical units. There are opportunities  for collaboration with Indian Statistical Institute as well as Ministry of Statistics and Program Implementation (MOSPI). Now Biostatistics and  Epidemiology are emerging areas for health sciences research with the frequent emergence of new lifestyle diseases and communicable diseases like Cancer, AIDS, SARS, H1N1, Bird Flu, COVID, etc. Stochastic Process Modeling and Exploratory Data Analysis are thrust areas of research identified by DST..

.  Interdisciplinary  emerging applied areas like Clinical Trials, Data Analytics,  R programming and Python, Epidemiology, Survival Analysis, Risk Modeling,  Multivariate Analysis Methods, Spatial Modeling and Neural Networks,  Demography and Population Studies, Statistical Genetics and Ecology, Biodiversity and Environmental Studies, Computational Biology,  Genomics and Microarray Modeling, Industrial Quality Control,  Reliability Modeling, Statistical Physics and Chemistry, Stochastic Modeling, Time Series Modeling,  Official Statistics and Development Planning etc are part of  the curriculum for M.Sc. Statistics.

This programme will nurture an analytical mind for gathering information from real data and abstract thinking as well as stochastic modeling of natural phenomena which is much affected by random causes rather than deterministic factors.  Now statistics and data analytics are becoming essential tools for engineering and technology as well as Health and Business management. Remote sensing, signal processing, Cluster Analysis, Discriminant Analysis etc are statistical techniques widely used in space technology, geographical surveys and disease mapping. Proper statistical education with data analytical skills are necessary for these. Decision making in every field is data driven for which expert statisticians are to be developed.

Various Workshops, Training Programs, National/ International Seminars and Conferences will be organized for the benefit of faculty  and students. MoUs and Linkages will be signed with reputed industries and research institutes for providing opportunities for collaboration and on-the-job training in emerging areas.

Links:

The Program Structure: M.Sc. Statistics

Revised MSc Mathematics Syllabus 2021

Revised MSc Statistics Syllabus 2021

 

Course Code Course Title Teaching   L+T+P Credits
SEMESTER I                                            Total Credits     24
SMS MP C01 Mathematical Tools for Statistics 4 +0+0 4
SMS MP C02 Probability Theory I 4 +0+0 4
SMS MP C03 Statistical Distribution Theory 4 +0+0 4
SMS MP C04 Statistical Estimation Theory 4 +0+0 4
SMS MP C05 Sampling Techniques & Official Statistics 4 +0+0 4
SMS MP C06 Statistical Computing I ( in  R) 3+0+2 4
SEMESTER II                                           Total Credits     24
SMS MP C07 Probability Theory II 4 +0+0 4
SMS MP C08 Testing of Hypotheses 4 +0+0 4
SMS MP C09 Design of Experiments 4 +0+0 4
SMS MP E01 Elective 1 4 +0+0 4
SMS MP E02 Elective 2 4 +0+0 4
SMS MP C10 Statistical Computing  II ( in Python) 3 +0+2 4
SEMESTER III                                         Total  Credits    24
SMS MP C11 Multivariate Statistical Analysis 4 +0+0 4
SMS MP C12 Stochastic Processes  Modeling 4 +0+0 4
SMS MP E03 Elective 3 4 +0+0 4
SMS MP E04 Elective 4 4 +0+0 4
SMS MP C13 Advanced Statistical Computing  (R and Python / SPSS & SAS) 2 +0+2 4
Open Course 4 +0+0 4
SEMESTER IV                                         Total Credits     16
SMS MP E05 Elective 5 4 +0+0 4
SMS MP C14 Project  Work / Dissertation(in a reputed research institute / department / industry) 20 8
SMS MP C15 Project Report / Dissertation Presentation  & Viva Voce 4
Grand Total of Credits 88

 

N.B. 1 In the present Program Structure there are 15 Core Courses with a total of 64 credits, 5 Elective courses with a total of 20 credits and an Open Course of 4 credits so that the grand total of credits is 88 for the whole program.  Open Course is any course offered by a Department / School / Inter University Centre of the University other than the parent Department / School/ Centre, permitted by both Departments / Schools to encourage interdisciplinary studies and research in emerging areas. Students can select an open course with the permission of the Head of the Department / Director of the School in accordance with the CSS regulations 2020 of the university.

N.B. 2   In case students wish to undergo online MOOC Courses in SWAYAM PORTAL or offered by IITs and other reputed institutes of national importance, they can choose them as electives during Semester 3 and 4 with the permission of the Head of the Department / Director of the School in accordance with the CSS regulations  2020 of the university.

N.B. 3    Project / Dissertation shall be carried out by each student, in a reputed research institute/ department or industry under the joint supervision of an internal faculty and external guide / expert approved by the Director/ Faculty Advisor.  Initial works like literature survey, review of literature etc may be started at the end of Semester II itself and a brief report should be submitted at the end of  Semester III.

The students have to submit a bound copy and soft copy of the Project Report (documented in LaTex) of at least 50 pages certified by the supervisors, at least 7 days before the conduct of the Presentation and Viva Voce. There will be interim report presentations on the progress of work and will be part of  continuous internal assessment. The Project/ Dissertation will be valued with respect to various criteria including content and presentation as decided by the University/ Department/School as per CSS  Rules & Regulations 2020.

Table of Elective Courses ( 3 streams ):

 Students can select any 5 elective courses with at least one  from each  of the groups A, B, C of electives given below, in consultation with the  Head of the Dept / Faculty Coordinator. More electives may be added and offered with the permission of the competent authorities.

Course Code NAME OF THE COURSE Teaching Credits
GROUP A: DATA  SCIENCE &  DATA ANALYTICS
EA1 Applied Regression Analysis 4 4
EA2 Bayesian Inference and Computing 4 4
EA3 Data Science &  Big  Data  Analytics 4 4
EA4 Data Mining Techniques 4 4
EA5 Machine  Learning  &  Predictive Modeling 4 4
EA6 Advanced Resampling Techniques 4 4
EA7 Time Series Analysis & Forecasting 4 4
EA8 Bioinformatics and Computational Biology 4 4
GROUP B:  DEMOGRAPHY &  BIOSTATISTICS
EB1 Survival Analysis 4 4
EB2 Biostatistics & Epidemiology 4 4
EB3 Demography & Population Dynamics 4 4
EB4 Categorical  &  Directional Data Analysis 4 4
EB5 Clinical Trials and Bioassays 4 4
EB6 Statistical Genetics and Ecology 4 4
EB7 Statistical Methods for  Micro-Array  Analysis 4 4
GROUP C: INDUSTRIAL  & FINANCIAL APPLICATIONS
EC1 Operations Research 4 4
EC2 Industrial Statistics &  Quality Control 4 4
EC3 Actuarial Statistics 4 4
EC4 Econometric Methods 4 4
EC5 Stochastic Finance 4 4
EC6 Reliability Modeling and Analysis 4 4
EC7 Advanced Distribution Theory 4 4
EC8 Mixture Regression Analysis 4 4

Process of Evaluation:

The admission and evaluation are guided by CSS Regulations 2020 approved by M.G.University and subsequent amendments if any. The internal assessment will be a continuous assessment (CA) that accounts for 40% of the  evaluation in both theory and practical. The end semester examination will account for the remaining 60% of the evaluation.

End-Semester Examination: The end semester examination will account for 60% of the evaluation. The evaluation of the end-semester examination of the first and third semesters shall be done by the faculty who taught the course. Evaluation of the 2nd and 4th semester courses based on questions set by external question paper setters shall be evaluated by two examiners; one, the external (as far as possible the question paper setter shall evaluate the examination paper as well) and the other, internal examiner.

The double valuation of answer scripts in the second and the fourth semester courses shall be done by external examiners and the concerned faculty respectively as approved by the Faculty Council.

The Head of the School/Department/Centres/Institutes will make arrangements for the evaluation of the answer scripts. The project/dissertation shall be evaluated by two examiners, one of them the faculty member who supervised the project and the other an external examiner to be decided by the HOD from a panel recommended by faculty council and approved by the Vice Chancellor. The comprehensive viva-voce, if any, must be carried out along with project evaluation.

Continuous Assessment (CA): The student’s participation and classroom performance as well as the feedback received from tests, tutorials, assignments and term papers shall form the basis for continuous assessment (CA). It accounts for 40% of the evaluation in both theory and practical. This assessment shall be based on a predetermined transparent system involving periodic written tests, assignments and seminars in respect of theory courses and based on tests, lab skill, records/viva and attendance in respect of practical courses.

The percentage of marks assigned to various components for internal evaluation is as follows:

  1. Theory
Component % of internal marks
i. Test papers 50%
ii. Assignments/Book review/debates 25%
iii. Seminars/Presentation of case study 25%

For each course there shall be at least two class tests during a semester. Average of the best of the marks obtained in the two tests (in the case of more than two tests) or the average of the tests ( if there is only two tests)  will be counted as the internal test component of CA.

Practical

Component % of internal marks
i. Lab skill 25%
ii. Records 25%
iii. Test papers 40%
iv. Viva Voce 10%

 Test Paper:

Valued answer scripts shall be made available to the students for perusal within 10 working days from the date of the tests.

Assignments:

Each student shall be required to do 2 assignments/book reviews for each course. Assignments/book review after valuation must be returned to the students. The teacher shall define the expected quality of the above in terms of structure, content, presentation and the like, and inform the same to the students. Punctuality in submission of assignments/records is to be given a weightage in the internal evaluation.

Seminar:

Every student shall deliver one seminar as an internal component of every course and must be evaluated by the respective course teacher in terms of structure, content, presentation and interaction. The soft and hard copies of the seminar report are to be submitted to the teacher in charge.

Results of Continuous Assessment:

The results of the CA counter-signed by Head of the school shall be displayed on the notice board 5 days before the end semester examinations. The marks awarded for various components of the CA shall not be rounded off, if it has a decimal part. The total marks of the CA shall be rounded off to the nearest whole number. Relevant records of continuous assessment (CA) must be kept in the department and that must be made available for verification.

Project Work:

There shall be a project/dissertation to be undertaken by all students. The dissertation entails field work, lab work, report writing, presentation and viva voce. The class hours allotted for project work may be clustered into a single slot so that students can do their work at a centre /location for a continuous period of time. However, appropriate changes can be made by the faculty council in this regard. Project/dissertation shall be carried out under the supervision of a teacher in the parent School/Centre/Institute or other research institutes or industrial establishment or university departments if they permit the students to do so, after getting permission from the Department Head.

In such cases, one of the teachers from the schools/centres/institutes would be the co- supervisor/internal guide and an expert from the industry/ research organization concerned shall act as supervisor/ external guide. In the case of M Phil programme while forwarding the mark lists of the second semester to the CSS, director of the school/centre/institute shall ensure that both the hard and soft copies of the project/dissertation of all students will be handed over to the University Library immediately after the publication of the results.

External Evaluation of Theory Answer Scripts:

The external evaluation shall be done after the examination at the earliest, preferably in a centralized valuation. As far as possible bar coded Answer Books shall be used to ensure confidentiality. The evaluation of the answer scripts shall be done by examiners based on a well-defined scheme of valuation. End semester evaluation of  Theory Answer Scripts shall be conducted and evaluated by one internal examiner for odd semesters. For even semesters, one external and one internal examiner shall do the process of evaluation. That is, there shall be double valuation system of answer books in the 2nd and 4th Semester evaluations. The final marks awarded will be the average of both valuations. If there is a variation of more than 10 % of the maximum marks, the answer books shall be valued by a third external examiner appointed by the director. The final marks to be awarded shall be the average of the nearest two best out of three awarded by  all  the examiners.

PATTER OF QUESTION PAPER FOR THEORY

PART No. of Questions No. of Questions to be answered Marks Total Marks Type of Question Taxonomy
A 12

( 3 from each unit)

8 5 40 short answer type

(maximum 1  page)

Remember Understand

Application

B 4 (2 each from Units 1 and 2) 2 15 30 long answer type

(about 2-3 pages)

Analytical

Application Creative

C 4 (2 each from Units 3 and 4) 2 15 30 long answer type

(about 2-3 pages)

Creative Application Analytical
Total 20 12 100

 INTERNAL EVALUATION

Internal Evaluation will be conducted as Continuous Assessment according to CSS Guidelines 2020 and will consist of Test Papers, Assignments and Seminars / presentations for theory courses.  For Practical Courses timely submission of   practical records, test papers,   lab skills in practical works, Viva Voce / presentations etc are important components.