FREE IGNOU MSCAST Solved Assignment 2025–26 Download
If you are a student of the Master of Science (Applied Statistics) (MSCAST) programme at IGNOU, you already know how important assignments are for scoring high grades and successfully completing the course. As a student with 2 years of experience in the IGNOU MSCAST programme, I have gained in-depth knowledge about the structure, pattern, and evaluation of MSCAST assignments. Over the years, my team and I have helped thousands of IGNOU students prepare high-quality solved assignments, and we have now delivered 2392+ IGNOU MSCAST solved assignments with excellent feedback.
The IGNOU MSCAST Solved Assignment 2025-26 session is designed to help students understand the complete guidelines, formatting rules, and solutions required to score top marks. Many students struggle with assignment preparation because the questions require conceptual clarity, analytical writing, statistical calculations, R/Python programming, and proper IGNOU formatting. This is exactly where our expertise becomes helpful.
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🔥 IGNOU MSCAST Solved Assignment 2025–26: Complete Course List
Below is the updated table of all courses included in the IGNOU MSCAST Programme (2025-26 Session).
I Year (First Semester)
| Course Code | Title of the Course | Nature | Credits |
|---|---|---|---|
| MST 011 | Real Analysis, Calculus and Geometry | Theory | 2 |
| MST 012 | Probability and Probability Distributions | Theory | 4 |
| MST 013 | Survey Sampling and Design of Experiments-I | Theory | 4 |
| MST 014 | Statistical Quality Control and Time Series Analysis | Theory | 4 |
| MST 015 | Introduction to R Software | Theory | 2 |
| MSTL 011 | Statistical Computing using R-I | Lab | 4 |
I Year (Second Semester)
II Year (Third Semester)
| Course Code | Title of the Course | Nature | Credits |
|---|---|---|---|
| MST 020 | Survey Sampling and Design of Experiments-II | Theory | 4 |
| MST 021 | Classical and Bayesian Inference | Theory | 4 |
| MST 022 | Linear Algebra and Multivariable Calculus | Theory | 4 |
| MST 023 | Research Methodology | Theory | 4 |
| MSTL 013 | Statistical Computing using R-III | Lab | 4 |
II Year (Fourth Semester)
| Course Code | Title of the Course | Nature | Credits |
|---|---|---|---|
| MST 024 | Data Analysis with Python | Theory | 2 |
| MSTL 014 | Data Analysis with Python Lab | Lab | — |
| MST 025 | Categorical and Survival Analysis | Theory | — |
| MST 026 | Introduction to Machine Learning | Theory | — |
| MSTL 015 | Statistical Computing using R-IV | Lab | — |
| MSTE 011 | Operations Research* | Theory | — |
| MSTE 012 | Stochastic Processes* | Theory | — |
| MSTP 011 | Project/Dissertation* | Project | — |
(*Elective Courses)
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Understanding the Question
We break down every question into parts and analyze what the evaluator expects. -
Statistical Explanation with Examples
The solutions include simplified statistical concepts for maximum clarity. -
Graphical and Computational Support
R outputs, Python snippets, plots, and codes are provided where necessary. -
IGNOU Format Compliance
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A4 size
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1.5 spacing
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Proper margins
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Handwritten/typed formats based on student requirement
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Plagiarism-Free Answers
Our solved assignments are written from scratch — no copy-paste from internet sources.
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