Master of Science (Applied Statistics) at Indira Gandhi National Open University

INR 30,800

Indira Gandhi National Open University, IND

Type: Masters Duration: 2.0 years

Explore the Master of Science (Applied Statistics) program at Indira Gandhi National Open University. This program is offered in IND and provides an excellent learning opportunity in Masters studies.

The Master of Science in Applied Statistics at Indira Gandhi National Open University is a two-year program designed to equip students with both theoretical knowledge and practical skills in statistics. The curriculum is structured around a semester system and focuses on core and advanced statistical concepts, including real analysis, probability distributions, and statistical computing using R. Students will engage in project work, enhancing their ability to apply statistical tools to real-world problems. The program targets working professionals in various fields such as data science, management, and academia, as well as graduates seeking to deepen their understanding of statistics. With a fee of Rs. 15,400 per annum, this program offers a comprehensive education in statistics, preparing graduates for career advancement and further studies in the field.

University
Indira Gandhi National Open University
University Location
IND (Online)
Program Duration
2.0 years
Ranking
Not available
Part-time allowed
Yes

Required Courses
  • Real Analysis, Calculus and Geometry
  • Probability and Probability Distributions
  • Survey Sampling and Design of Experiments-I
  • Statistical Quality Control and Time Series Analysis
  • Introduction to R Software
  • Statistical Computing using R-I
  • Statistical Inference
  • Applied Regression Analysis
  • Multivariate Analysis
  • Epidemiology and Clinical Trials
  • Statistical Computing using R-II
  • Survey Sampling and Design of Experiments-II
  • Classical and Bayesian Inference
  • Linear Algebra and Multivariate Calculus
  • Research Methodology
  • Statistical Computing using R-III
  • Data Analysis with Python
  • Data Analysis with Python Lab
  • Categorical and Survival Analysis
  • Introduction to Machine Learning
  • Statistical Computing using R-IV
  • Project/Dissertation
Elective Courses
  • Operations Research
  • Stochastic Processes