Provides a comprehensive introduction to research methodology, experimental design, statistical analysis, and scientific publication practices. The course is divided into five chapters.
Chapter 1 introduces the foundations of research, including methods of acquiring knowledge (tenacity, authority, intuition, and science), the distinction between science and technology, inductive and deductive reasoning, and key scientific concepts such as hypothesis, theory, law, fact, and the scientific method. It also covers cause-and-effect relationships and the formulation of research hypotheses.
Chapter 2 focuses on experimental research, addressing validity (internal and external), the core principles of experimentation—randomization, replication, and blocking—classification of experiments (true experiments, quasi-experiments, ex post facto), sampling methods, possible errors (random and systematic), and descriptive versus inferential statistics.
Chapter 3 covers academic publications and databases, including classification systems (DDC, LCC, UDC), types of publications (primary, secondary, tertiary), academic search engines (Google Scholar, Scopus, Web of Science), citation indexes, and citation analysis metrics such as impact factor, CiteScore, h-index, and g-index. It also provides guidance on conducting a literature review.
Chapter 4 addresses the preparation of research papers, focusing on the IMRAD structure (Introduction, Materials and Methods, Results, Discussion), selecting appropriate journals, and understanding plagiarism (types and avoidance strategies).
Chapter 5 presents practical experiment design exercises, including population distributions, means and variances, decision-making elements, outlier detection using Grubbs' test, and complete factorial experiments leading to regression equations. Each chapter includes learning outcomes and practice exercises to reinforce understanding.