<p style="text-align:justify">This book on Research Methodology in Veterinary and Animal Sciences represents a synthesis of traditional veterinary and animal science expertise and modern computational intelligence including Generative AI. The conceptual framework, selection of pedagogical topics, and logical flow were meticulously curated&nbsp;through a reasonable review of foundational veterinary literature and research methodology.</p> <p style="text-align:justify">While generative AI (Google Gemini) was utilized to draft initial explanations and structure complex data, every chapter has been manually reviewed, edited, and verified by the author for clarity, scientific accuracy, clinical relevance, and adherence to academic standards. The author maintains full responsibility for the content, interpretations, and conclusions presented herein.</p>

Dr. M. Murugan is a Professor and Head of the Department of Livestock Production Management at the Veterinary College and Research Institute, Tirunelveli (TANUVAS). With 25 years of extensive experience spanning teaching, research, and extension services, he brings a wealth of practical and academic knowledge to the field of veterinary and animal production sciences. In addition to his technical expertise, Dr. Murugan holds an MBA in Human Resource Management, providing him with a unique perspective on organizational and research management. A prolific content creator and widely published author in reputable national and international journals, he is dedicated to advancing livestock production through rigorous scientific inquiry and education.

Dr. V.S. Abbiramy is an Assistant Professor in the Department of Computer Science at Sarah Tucker College, Tirunelveli. With two decades of experience in teaching and research, she has dedicated her career to the applications of computer science for both undergraduate and postgraduate education. Dr. Abbiramy specializes in Database Management Systems (DBMS), Image Processing, and Artificial Intelligence. Her work focuses on leveraging AI tools to enhance research outcomes and creating high-quality educational content, making her an invaluable contributor to the integration of data science within the veterinary and animal science domains.

<p style="text-align:justify"><strong>Chapter 1.</strong> Research Methodology<br /> <strong>Chapter 2.</strong> Research Problem<br /> <strong>Chapter 3.</strong> Research Design<br /> <strong>Chapter 4.</strong> Sampling Design<br /> <strong>Chapter 5.</strong> Measurement and Scaling Techniques<br /> <strong>Chapter 6.</strong> Methods of Data Collection<br /> <strong>Chapter 7.</strong> Sampling Fundamentals<br /> <strong>Chapter 8.</strong> Processing and Analysis of Data<br /> <strong>Chapter 9.</strong> Skewness and Correlation<br /> <strong>Chapter 10.</strong> Testing of Hypotheses<br /> <strong>Chapter 11.</strong> Efficiency of Diagnostic Tests<br /> <strong>Chapter 12.</strong> Research Report Writing<br /> <strong>Chapter 13.</strong> Computer Software in Data Analysis<br /> <strong>Chapter 14.</strong> Annexure<br /> <strong>Chapter 15.</strong> Exercises for Practice<br /> <strong>Chapter 16.</strong> Abbreviations<br /> <strong>Chapter 17.</strong> References</p>