MST 011 Real Analysis, Calculus and Geometry | Guess Papers of IGNOU 
MST 012 Probability and Probability Distributions | Guess Papers of IGNOU 
MST 013 Survey Sampling and Design of Experiments-I | Guess Papers of IGNOU 
MST 014 Statistical Quality Control and Time Series Analysis | Guess Papers of IGNOU 
MST 015 Introduction to R Software | Guess Papers of IGNOU 
MST 016 Statistical Inference | Guess Papers of IGNOU 
MST 017 Applied Regression Analysis | Guess Papers of IGNOU 
MST 018 Multivariate Analysis | Guess Papers of IGNOU 
MST 019 Epidemiology and Clinical Trials | Guess Papers of IGNOU 
MST 020 Survey Sampling and Design of Experiments-II | Guess Papers of IGNOU 
MST 021 Classical and Bayesian Inference | Guess Papers of IGNOU 
MST 021 Classical and Bayesian Inference | Guess Papers of IGNOU 
MST 022 Linear Algebra and Multivariate Calculus | Guess Papers of IGNOU 
MST 023 Research Methodology | Guess Papers of IGNOU 
MST 024 Data Analysis with Python | Guess Papers of IGNOU 
MST 026 Introduction to Machine Learning | Guess Papers of IGNOU 
MSTE 011 Operations Research | Guess Papers of IGNOU 
MSTE 012 Stochastic Processes | Guess Papers of IGNOU 
MST 025 Categorical and Survival Analysis| Quick...
Rs.149
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Rs.50
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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, English |
| Author | : BMAP EDUSERVICES PVT LTD |
| Publisher | : BMAP EDUSERVICES PVT LTD |
| University | : IGNOU (Indira Gandhi National Open University) |
| Pages | : 50 |
| Weight | : 157gms |
| Dimensions | : 21.0 x 29.7 cm (A4 Size Pages) |
MST 025 Categorical and Survival Analysis is a crucial course in the Master of Science (Applied Statistics) program, designed to equip students with advanced skills in analyzing categorical data and survival analysis. This course covers a broad spectrum of topics, including logistic regression, contingency tables, Kaplan-Meier estimator, and Cox proportional hazards model. These techniques are invaluable for tackling complex data structures and conducting rigorous statistical research.
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