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Updated on 15 Sep, 2023


M.Sc. (Applied Statistics) (MSCAST)

Minimum Duration: 2 Years
Maximum Duration: 4 Years
Course Fee: Rs. 30,800
Minimum Age: No bar
Maximum Age: No bar

Eligibility:

Graduate with B.A./B.Sc. degree with Statistics/Mathematics as one of the subjects from any recognised University/Institution/Organisation.

 

Medium of Instruction: The medium of instruction is English. The course material is in English only.

Exit Option: After successfully completing first two semesters, learner will be awarded Post Graduate Diploma in Statistics and Applications (PGDSA).

Note: The Programme is on offer from July 2023 admission cycle onwards
 

The School of Sciences has developed the M.Sc. (Applied Statistics) programme with the help of several eminent experts across India. Applied Statistics is an emerging field which deals with acquisition, representation, analysis and interpretation of data. The demand for statistics professionals is increasing day by day due to its applications potential in several fields such as rural and urban planning, data monitoring, natural resources management, management of industrial and business problems and social and agricultural development, etc. To cope up this increasing demand, the M.Sc. (Applied Statistics) programme has been developed which caters the needs of working professionals and graduates aspiring for employment in industries (e.g., software, core and applied industries, medicine, and pharmaceutical industries), National Laboratories, R & D Organisations and Academic Institutions (Science and Technology, Engineering and Medical Colleges and Universities, etc.). This programme emphasises on the courses which have vast potential for applications of statistical tools in Industrial, Business, Management, Medical, Research oriented fields, Data Science, Machine Learning, etc. This programme has been built around detailed concepts/skills processes at the basic level to make it easy to understand how Statistics can be put to practical use. The programme has been designed to make you aware of the theories and applications of Statistics. Hands-on training is provided in the lab courses to familiarise you with the applications of statistical tools with the help of open-source software like R and Python. This programme is especially useful for the working professionals who are interested in updating their knowledge in Statistics. It would also help fresh Graduates, who wish to continue their education and are interested in getting into the field of Applied Statistics.
 
Programme Objectives
This programme has been designed in view of NEP 2020 with a semester approach in mind. This programme is aimed at theoretical knowledge and practical skills development in core and advanced statistics courses for providing conceptual framework as well as focused on the project/dissertation work. The objectives of this programme are to:
Ø provide core knowledge of statistics required for applications.
Ø familiarise with the real-life problems to the learners and make them able to apply various statistical tools.
Ø equip them with the skills of using appropriate software for statistical applications in various fields.
Ø provide opportunities for career progression and higher education in statistics.
 
Target Group:
Ø Working professionals in data science departments, management departments, software industries, pharmaceutical industries, national laboratories, R&D organisations, academic institutions/colleges/universities, agricultural fields, etc.;
Ø College/university teachers either teaching or interested to teach statistics related courses;
Ø Working professionals possessing basic or no exposure to applied statistics but are interested to initiate and develop skills in this field; and
Ø Graduates with statistics/mathematics interested to acquire theoretical understanding and develop practical skills on the aspects of data analysis.
 
Programme Structure and Details
This is a two-year Master’s degree programme in Applied Statistics, which is offered in both January and July cycles of admission. The programme has been divided into two semesters per year (July to December and January to June). This programme comprises 16 core and compulsory theory courses worth total 54 credits and 5 core and compulsory lab courses worth 18 credits. There is one project/dissertation worth 8 credits and 2 theory courses worth 4 credits each which can be taken together instead of project/dissertation. To successfully complete this programme, you will have to earn 80 credits over a period of 2 to 4 years depending on your convenience. The theory courses are designed to provide the basic knowledge and techniques of statistics, which are necessary for applications in various areas. These theory courses will help you in studying the lab courses well. The lab courses have been designed in this programme separately and each semester has one lab course which has been developed based on the theory courses of that semester. After successfully completing the first two semesters, you will be awarded the PG Diploma in Statistics and Applications.
The detailed structure of the MSCAST programme is as follows:
 
Programme Structure
Course Code
Course Title
Credits
Nature of Course
(Theory / Lab)
Core/Elective
Semester I
MST-011
Real Analysis, Calculus and Geometry
02
Theory
Core
MST-012
Probability and Probability Distributions
04
Theory
Core
MST-013
Survey Sampling and Design of Experiments-I
04
Theory
Core
MST-014
Statistical Quality Control and Time Series Analysis
04
Theory
Core
MST-015
Introduction to R Software
02
Theory
Core
MSTL-011
Statistical Computing using R-I
04
Lab
Core
 
Total Credits
20
 
 
Semester II
MST-016
Statistical Inference
04
Theory
Core
MST-017
Applied Regression Analysis
04
Theory
Core
MST-018
Multivariate Analysis
04
Theory
Core
MST-019
Epidemiology and Clinical Trials
02
Theory
Core
MSTL-012
Statistical Computing using R-II
06
Lab
Core
 
Total Credits
20
 
 
Semester III
MST-020
Survey Sampling and Design of Experiments-II
04
Theory
Core
MST-021
Classical and Bayesian Inference
04
Theory
Core
MST-022
Linear Algebra and Multivariate Calculus
04
Theory
Core
MST-023
Research Methodology
04
Theory
Core
MSTL-013
Statistical Computing using R-III
04
Lab
Core
 
Total Credits
20
 
 
Semester IV
MST-024
Data Analysis with Python
02
Theory
Core
MSTL-014
Data Analysis with Python Lab
02
Lab
Core
MST-025
Categorical and Survival Analysis
02
Theory
Core
MST-026
Introduction to Machine Learning
04
Theory
Core
MSTL-015
Statistical Computing using R-IV
02
Lab
Core
MSTE-011
Operations Research*
04
Theory
Elective (To be taken together)
MSTE-012
Stochastic Processes*
04
Theory
MSTP-011
Project/Dissertation*
08
 
Elective
 
Total Credits
20
 
 
Learner may opt either two theory coursesOperations Research” (4 credits) and “Stochastic Processes” (4 credits) together or a Project/Dissertation.
 
Learner Support Centres:
Learner Support Centres presently activated for the PGDAST programme are expected to be offering the MSCAST programme, which are currently located across several regions. However, there may be change in the list of centres. University may allot a study centre to the enrolled learners at its discretion in case of any issue.
 
 
Programme Coordinators:
Dr. Neha Garg and Dr. Prabhat Kumar Sangal
Email: mscast@ignou.ac.in,
Ph.: 011-29572830; 011-29572829

 

 

 

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[Updated on 05-Jun-2024]