AST-01 IGNOU Guess Paper 2026-27

Course Scope & Syllabus Overview for AST-01: Statistical Techniques

AST-01: Statistical Techniques is a core course under the Applications-Oriented Courses (School of Humanities, IGNOU), designed to equip students with foundational and advanced statistical methodologies essential for linguistic and literary analysis. The syllabus bridges theoretical probability and practical data interpretation, emphasizing real-world applications in research methodologies, corpus analysis, and quantitative literary studies. This course aligns with IGNOU’s CBCS framework, ensuring students develop critical skills in hypothesis testing, regression analysis, and sampling techniques—tools vital for empirical work in humanities disciplines.

Key Syllabus Units & Topics

• Block-1 Statistics and Probability: Covers fundamental concepts such as descriptive statistics, probability distributions (binomial, Poisson, normal), and their applications in linguistic data modeling. The unit also introduces combinatorial probability and its relevance to corpus-based research.
• Block-2 Statistical Inference: Focuses on estimation techniques (point and interval), confidence intervals, and hypothesis testing (parametric and non-parametric). Students explore t-tests, chi-square tests, and ANOVA, with emphasis on their use in validating linguistic hypotheses.
• Block-3 Applied Statistical Methods: Delves into regression analysis (linear and multiple), correlation coefficients, and time-series analysis. Practical case studies from literary and linguistic research demonstrate how these methods derive insights from textual data.
• Block-4 Sampling: Examines sampling theory, stratified and cluster sampling, and non-probability sampling techniques. The unit critiques sampling biases and designs methodologies for representative linguistic data collection.

Frequently Asked Questions

Q: How are marks distributed in the AST-01 Term-End Examination (TEE), and what weightage do assignments carry?
A: The TEE for AST-01 carries 100 marks, with assignments accounting for 30% of the total evaluation (30 marks). Focus on both theoretical concepts and practical application, as questions often blend statistical theory with real-world examples from humanities research.

Q: Are there recurring themes or question patterns in past AST-01 TEE papers, and how can I prioritize revision?
A: Past papers reveal a recurring emphasis on regression analysis, hypothesis testing, and sampling techniques. Prioritize revision by reviewing solved question papers from June/December cycles (2018–2023) to identify high-frequency topics, particularly those combining multiple units (e.g., Block-2 and Block-3).