MST 011 Real Analysis, Calculus and Geometry | IN-DEPTH STUDY GUID for IGNOU 
MST 011 Real Analysis, Calculus and Geometry | IN-DEPTH STUDY GUIDE for IGNOU 
MST 012 Probability and Probability Distributions | IN-DEPTH STUDY GUIDE for IGNOU 
MST 013 Survey Sampling and Design of Experiments-I | IN-DEPTH STUDY GUIDE for IGNOU 
MST 014 Statistical Quality Control and Time Series Analysis | IN-DEPTH STUDY GUIDE for IGNOU 
MST 015 Introduction to R Software | IN-DEPTH STUDY GUIDE for IGNOU 
MST 016 Statistical Inference| IN-DEPTH STUDY GUIDE for IGNOU 
MST 017 Applied Regression Analysis | IN-DEPTH STUDY GUIDE for IGNOU 
MST 018 Multivariate Analysis | IN-DEPTH STUDY GUIDE for IGNOU 
MST 019 Epidemiology and Clinical Trials | IN-DEPTH STUDY GUIDE for IGNOU 
MST 020 Survey Sampling and Design of Experiments-II| IN-DEPTH STUDY GUIDE for IGNOU 
MST 021 Classical and Bayesian Inference | IN-DEPTH STUDY GUIDE for IGNOU 
MST 022 Linear Algebra and Multivariate Calculus | IN-DEPTH STUDY GUIDE for IGNOU 
MST 023 Research Methodology | IN-DEPTH STUDY GUIDE for IGNOU 
MST 024 Data Analysis with Python | IN-DEPTH STUDY GUIDE for IGNOU 
MST 025 Categorical and Survival Analysis | IN-DEPTH STUDY GUIDE for IGNOU 
MST 026 Introduction to Machine Learning | IN-DEPTH STUDY GUIDE for IGNOU 
MSTE 011 Operations Research | IN-DEPTH STUDY GUIDE for IGNOU 
MSTE 012 Stochastic Processes | Quick Readable...
Rs.149
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| Category | : MASTER‘S DEGREE PROGRAMMES |
| Sub Category | : Master of Science (Applied Statistics) (MSCAST) |
| Products Code | : MSCAST-MST-S4-5.51 |
| HSN Code | : 490110 |
| Language | : English |
| Author | : BMAP EDUSERVICES PVT LTD |
| Publisher | : BMAP EDUSERVICES PVT LTD |
| University | : IGNOU (Indira Gandhi National Open University) |
| Pages | : 300 |
| Weight | : 199 GM |
| Dimensions | : 21.0 x 29.7 cm (A4 Size Pages) |
MSTE 012 Stochastic Processes is designed to provide students with a robust understanding of the theory and application of stochastic processes. This course covers key topics such as Markov chains, Poisson processes, Brownian motion, and renewal processes. It equips students with the knowledge and skills necessary to apply stochastic models to a variety of real-world problems.
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