Research Methodology and Data Analytics

Master of Science (M.Sc.)
Research Methodology and Data Analytics

Master of Science in Research Methodology and Data Analytics aims to produce master’s degrees with knowledge and skills in research, statistics, and information technology. The graduate expects to be able to apply advanced statistical methods to add value to data and to the search for new knowledge from existing information to be an effective researcher. The curriculum is organized by placing the learner at the center of learning. Develop learners in every way by having them solve problems and do research on their own, have morals, ethics, and professional ethics, and be ready to keep learning and growing after they graduate.

• The program provides teaching and learning of all courses in English, as well as writing thesis in English.
• The program emphasizes of integrated knowledge on data sciences and data analytics in a variety of fields.
• The program provides extracurricular activities for English skill development, such as seminar, encouraging students to join and present orally in both national and international conferences.
• The program recruited experts from foreign countries to be a permanent staff, and the program have collaborative network partners in foreign countries.
• The program have integrated knowledge and application of the use of mathematics, statistics, computer, in conducting research  effectively.

Students learn their research skills in a substantive field such as public health, climate science, marine or aquatic biology, land-use and development, social science, and population science, mining data from available websites such as the CRU, NREL, BOM and land-use data banks in Britain, the USA, Australia, and Thailand. They learn how to apply appropriate statistical methods, particularly those involving variation in time and space. These include generalized linear models (normal, logistic, Poisson and Gamma regression models), factor analysis and other multivariate procedures, GIS applications, and computational and graphical methods, and we develop new statistical methods where needed.

Expected Learning Outcomes (ELOs)

PLO1:  Design the research process using appropriate methodology for adding the value to the data in order to solve the organization issues
PLO2: Integrate the data manipulation knowledge to other disciplines in for adding the value to the data in order to solve the organization issues
PLO3: Select the appropriate tools and statistical methods for data analysis and adding the value to the data
PLO4: Express an open-minded and work with others both as a leader and as a follower
PLO5: Communicate the academic results with completeness and validity in both national and international levels
PLO6: Use technology for searching the information from several sources to continually improvement
PLO7: Possess morality, ethics in professional practice and in doing research

Lecturer or academician, private and government researcher, data analyst, statistician, data data analyst and manager, policy and planning  analyst, and others.

Plan A1
1. Graduated bachelor degree or equavalent with GPA not less than 3.00 or;
2. Graduated bachelor degree with GPA less than 3.00 and had research experience and must be considered by program committee;
3. Qualifications other than items 1 and 2 are at the discretion of the program committee. 

Plan A2
1. Graduated bachelor degree or equavalent with GPA not less than 3.00 or;
2. Qualifications other than item 1  are at the discretion of the program committee.

      Contact person: Asst. Prof. Dr. Rhysa McNeil (Program Chairperson)
      Phone :  0 7331 3928 – 45 ext. 1890
      Mobile: 087-288-2646
      Email:  rhysa.m@psu.ac.th