Quantitative Data Analysis in Scientific Research

The workshop “Quantitative Data Analysis in Scientific Research”, held on March 5, 2026, at Hoa Sen University’s Thanh Thai Campus Library, attracted many students, graduate students, and lecturers. Participants gained practical insights into key data analysis methods and how to apply them to research projects, theses, and academic reports.

Key Methods in Quantitative Data Analysis for Scientific Research

As part of a series of scientific research workshops for students, “Data Analysis in Scientific Research” took place at the Library, Thanh Thai Campus of Hoa Sen University (HSU). Taking place after the Lunar New Year holiday, it marked a fresh start for learning and research in the new year. Aligned with the program’s positive spirit and practical focus, the workshop drew strong participation from students, graduate students, lecturers, and staff from various departments, fostering a lively and open environment for academic exchange.

At the workshop, Mr. Dang Hoang Minh Quan, MA, HSU Lecturer at the Faculty of Business, shared systematic and practical perspectives on quantitative data analysis in scientific research.

With careful preparation and an enthusiastic instructing style, he not only introduced new concepts but also reviewed essential analytical methods, enabling participants to understand the material in a clear and logical manner. The session covered key topics, including identifying research data types and variables, the role of descriptive statistics in data summarization, and commonly used scale validation techniques such as Cronbach’s Alpha, EFA, and CFA.

Additionally, the speaker introduced a range of analytical techniques widely used in scientific research, such as correlation analysis, regression analysis, ANOVA, and SEM. Participants were guided on how to interpret statistical outputs and present research findings according to academic standards. Supported by his assistant, the speaker guided participants through hands-on exercises, giving them the opportunity to apply analytical methods to real datasets.

Although the session extended beyond the scheduled time, students, graduate students, lecturers, and staff remained highly engaged, actively participating in discussions and staying until the final moments.

Through this workshop, participants not only strengthen their knowledge of data analysis but also gain greater confidence in completing their research projects, theses, and academic reports.

As part of HSU’s ongoing initiatives to support student research, the program contributes to fostering an active academic environment and encouraging students to explore and develop their research skills.