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.

 

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.

 

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.

 

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:

 

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 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

 

 

Ø Counselling sessions may be conducted by the concerned Learner Support Centres depending upon availability of counsellors, lab facility, etc.

Ø Counsellor(s) at the activated Learner Support Centres would help learners to solve academic problem, if any. However, the counselling session would not be a lecture session.

Ø The MSCAST programme uses of free and open-source software (R and Python) so that learners can practice with the software even beyond the scheduled counselling hours at the Learner Support Centres and apply them in their work.

Ø Since this programme comprises laboratory courses, therefore, before applying for admission in the programme, learners should make sure that they will be able to attend the Theory and Practical counselling sessions and Term-end Practical Examination at the concerned Learner Support Centre activated and allotted for the programme.

 

 

Each of all theory courses of this programme will have 4-5 counselling sessions each of two hours for a 4-credit theory course and 2-3 counselling sessions each of two hours for a 2-credit theory course. The sessions for theory counselling are not compulsory to attend. But it is advisable to attend these sessions to clear your doubts and concepts.

 

The number of lab counselling sessions at the learner support centre should be as follows:

(i)      Lab counselling of 3 days (2 sessions per day each of 4 hours) should be compulsory      for 2 credits lab course.

(ii)     Lab counselling of 6 days (2 sessions per day each of 4 hours) should be compulsory      for 4 credits lab course.

(iii)    Lab counselling of 9 days (2 sessions per day each of 4 hours) should be compulsory      for 6 credits lab course.

 

Ø Learners should also make sure that they have access to computers because they will be required to carry out experiments on computers before attending the scheduled practical counselling sessions at their Learner Support Centre and complete the requirements.

Ø Learners should also have access to internet to download the software as prescribed in the practical course and communicate with the counsellors, coordinators, etc., if required.

 

 

Dr. Neha Garg and Dr. Prabhat Kumar Sangal

Email: mscast@ignou.ac.in, Ph.: 011-29572830; 011-29572829

 

Ø List of approved Learner Support Centres under a Regional Centre

Ø List of Approved Counsellors for the Learner Support Centres under the Regional Centre

Ø Schedule of the conduct of Laboratory Courses at the Learner Support Centres under the Regional Centre