BEY-014 IGNOU Solved Assignment 2026-27

Course Scope & Syllabus Overview for BEY-014: Statistical Methods

BEY-014: Statistical Methods is a core component of the Bachelor of Science (Applied Science-Energy) curriculum under IGNOU’s School of Engineering and Technology. This course equips students with foundational and advanced statistical techniques essential for data analysis, hypothesis testing, and decision-making in applied sciences. Designed within the CBCS framework, it bridges theoretical concepts with practical applications, ensuring students can interpret real-world datasets, apply inferential statistics rigorously, and align their solutions with IGNOU’s academic benchmarks. The course emphasizes both descriptive and inferential methodologies, preparing learners to tackle quantitative challenges in energy-related research and industry.

Key Syllabus Units & Topics

• Block-1: Descriptive Statistics: Covers data classification, measures of central tendency (mean, median, mode), dispersion (range, variance, standard deviation), and graphical representation techniques like histograms and box plots. Students learn to summarize and visualize univariate data effectively, forming the basis for deeper statistical analysis.
• Block-2: Summarisation of Bivariate and Multivariate Data: Focuses on analyzing relationships between two or more variables using correlation coefficients, regression analysis, and covariance matrices. This block teaches students to interpret associations, model dependencies, and apply multivariate techniques to complex datasets.
• Probability Distributions and Sampling Theory: Introduces discrete and continuous probability distributions (e.g., binomial, normal, Poisson), sampling methods, and the Central Limit Theorem. Concepts are grounded in practical scenarios to ensure students can design experiments and infer population parameters from samples.
• Hypothesis Testing and Estimation: Explores null hypothesis testing (t-tests, chi-square tests), p-values, confidence intervals, and Bayesian inference. Students gain proficiency in validating statistical claims and estimating parameters with precision, adhering to rigorous academic standards.
• Non-parametric Methods and Time Series Analysis: Covers rank-based tests (Mann-Whitney U, Kruskal-Wallis), goodness-of-fit tests, and introductory time series forecasting. This unit prepares students for scenarios where parametric assumptions are violated or sequential data analysis is required.

Frequently Asked Questions

Q: What is the marking scheme for the TMA in BEY-014, and how should students allocate word counts per section?
A: The TMA for BEY-014 carries 30 marks and requires strict adherence to IGNOU’s word limits: Section A (500 words) and Section B (250 words). Marks are distributed based on clarity, logical flow, and accuracy in applying statistical concepts, so precise adherence to word counts and structured answers is critical for full credit.

Q: Are there any specific pass marks or criteria for BEY-014 assignments, and how does it impact the final grade?
A: IGNOU does not publish pass marks for individual assignments, but assignments contribute 30% to the final grade. To excel, students must demonstrate a thorough understanding of statistical methods, correct application of formulas, and well-structured reasoning. Consistency in solving assignments aligns with the 40% internal assessment weightage, directly influencing the final grade card.