Research Methodology

Course Information

Instructor: Prof. Suparno Bhattacharyya
Email: suparno@iitism.ac.in
Office Location: Room No. 224A, Mechanical Engineering Department
Office Hours: Virtual, by appointment
Course Website: This website
Level: Master’s/Ph.D
Prerequisites: Coursework in Research Methodology

Course source code: GitHub

In Slide Form

Course Content

This course introduces students to the foundational principles of research methodology, with a focus on scientific and engineering contexts. It covers the essential stages of conducting research, beginning with the formulation of a clear and structured research problem. Students learn how to identify research gaps, develop hypotheses, and design strategies to investigate their questions systematically.

Emphasis is placed on understanding how to plan and execute a research study, including the collection and interpretation of data. The course also provides an introduction to the key statistical tools necessary for analyzing empirical findings and drawing meaningful conclusions, thereby preparing students to engage in rigorous, evidence-based inquiry.

Learning Outcomes

On successful completion of the course, students will be able to:

  1. Identify, design, and execute a research problem using various research processes and methodologies grounded in scientific and statistical tools.

  2. Apply various sample design techniques and their classification, recognise the characteristics of a good sample design, and select a sampling procedure for data collection.

  3. Distinguish among types of measurement scales, identify sources of error in measurement, and develop measurement tools to evaluate collected data.

  4. Use various methods of data collection while assessing the reliability and validity of the collected data.

  5. Prepare and present reports through different approaches for the dissemination of research outcomes.

  6. Employ the statistical tools necessary for designing a sample, analyzing data, and drawing scientific conclusions to arrive at a research outcome.

Course Materials

Textbooks

  1. Kothari, C. R., and Gaurav Garg. 2019. Research Methodology — Methods and Techniques. 4th ed. New Delhi: New Age International (P) Limited Publishers.

  2. Montgomery, Douglas C., and George C. Runger. 2016. Applied Statistics and Probability for Engineers. 6th ed.

  3. Kumar, Ranjit. 2018. Research Methodology: A Step-by-Step Guide for Beginners. 5th ed. SAGE Publications Ltd.

Software

Analyses and assignments use R and/or Python. Either environment is acceptable for the statistical components and the course project.

Course Format

The course is delivered through lectures combined with group work.

Assessment & Grading

Grade Components

Component Weight Format
Midterm Exam 30% Multiple-choice questions (MCQ)
End-Semester Examination 50% Long-answer type
Project Presentation 10% PowerPoint presentations in groups
Quiz 10% Pre-midsem quiz

Projects

The project requires students to formulate a research problem, collect or simulate data, and apply appropriate statistical tools to analyze the results. Emphasis is placed on correct interpretation of data and justification of conclusions using sound statistical reasoning. Students must present their work in the form of a structured research report and an oral presentation, following standard scientific communication practices.

Course Policies

Academic Integrity

Students are expected to uphold academic integrity in all coursework and research. All submissions must reflect the student’s own understanding and effort.

ImportantUse of AI Tools

The use of AI tools (e.g., ChatGPT, Copilot, Grammarly) is permitted only if explicitly allowed by the instructor. Any use must be properly disclosed, including the nature and extent of assistance. Unauthorized or undisclosed AI use — such as generating entire assignments, fabricating data, or bypassing individual work requirements — constitutes academic misconduct and is subject to disciplinary action per institutional guidelines. When in doubt, consult the instructor before using AI tools.

Accessibility & Accommodations

Students with documented disabilities, chronic medical conditions, or other special needs are encouraged to inform the instructor at the beginning of the semester to arrange appropriate accommodations. In the event of accidents, medical emergencies, or other unforeseen circumstances affecting attendance or coursework, students must notify the instructor promptly and provide official documentation (e.g., medical certificate, accident report, or institutional approval) to support requests for accommodations, extensions, or make-up work. Reasonable efforts will be made to ensure academic continuity in consultation with relevant institutional offices.

Communication

WarningEmail is the official channel

WhatsApp may be used by the instructor for broadcasting only. All other communication must happen via email — no other communication protocol will be entertained.

Key Dates

Event Date
Midterm 27 February – 03 March, 2026
Project due 11th & 12th April, 2026 (tentative)
End-Sem Examination 26 April – 03 May, 2026
Holidays / No class Consult the Academic Calendar