M.Sc. Applied Statistics

K. J. Somaiya College of Science and Commerce, Department of Statistics has announced a new course in M.Sc. Applied Statistics.

Need for M.Sc. Applied Statistics course

In Mumbai,  M.Sc. Statistics course is available only at Mumbai University and a few other institutes. All these institutes are located in the western suburbs of Mumbai. No college on Central suburbs of Mumbai teaching this M.Sc. Applied Statistics course.
Every year only 120 students get admission for M.Sc. Statistics course due to the limited number of seats in Mumbai for this course.
Statistics is an interdisciplinary subject. There is a huge demand for statisticians in industries, academics and research work for data analysis.
Machine learning and Artificial intelligence are emerging areas where a huge number of statisticians is required.

Learning outcome

The underlying philosophy of the M.Sc. Statistics course is to develop the theoretical and analytical skills of the students so that they may be absorbed in the corporate world or be able to pursue higher research work in Statistics.

By the end of the course, learners should be able to:

  • define statistical terms
  • comprehend statistical concepts and relationships in the economic and social aspects among others
  • interpret, use and present information in written, graphical, diagrammatic and tabular terms
  • deduce and infer through manipulation of statistical expressions
  • enable efficient use of statistical software such as SPSS, Python, R etc. to solve statistical problems
  • develop the ability to use statistical knowledge and skills in other disciplines
    stimulate the exercising of value decisions/judgments based on the scientific approach
  • acquire a suitable foundation for further studies and related disciplines
    appreciate the beauty and crucial role of statistics in national development

Job opportunities and Industries 

Statistics being an interdisciplinary subject, a good number of jobs are available in various fields such as academics, agriculture, pharmaceuticals, biostatisticians, information technology, machine learning, artificial intelligence etc.