Quantitative Research Methods
Quantitative Research methods play a key role in the discovery of new knowledge and the evaluation of tools and technologies across many disciplines. Quantitative methods use mathematical, statistical or numerical techniques to process numerical data. Examples and hands-on demonstrations will be provided with R or Python programming languages. The goal of this module is to provide basic principles and foundations of commonly-used quantitative research methods that can be applied in multiple disciplines, including Software Engineering, Cybersecurity and Human-Centred Computing.
Workshop (Face-to-Face or Webinar)
Dr. Kla Tantithamthavorn (Email: firstname.lastname@example.org)
By the end of this module, students will
|26 April 2023 10:00-12:00 pm
|Lecture #1: Introduction to Quantitative Research Methods and Design Science Paradigms
|28 April 2023 10:00-12:00 pm
|Lecture #2: Statistical Analysis (Parametric and Non-parametric Tests), Hypothesis Testing and Effect Size Analysis
|5 May 2023 10:00-12:00 pm
|Lecture #3: Modern Regression Analysis (Linear, Non-Linear, Logistic) and Correlation vs Causation + Modern Model Explainability
|10 May 2023 10:00-12:00 pm
|Lecture #4: Modern Machine Learning for Data Analysis and Common Pitfalls and Avoidance Strategies
Slack will be used for all announcements, general questions about the course, clarifications about assignments, student questions to each other, discussions about material, and so on.
We strongly encourage all students to participate in discussion, ask, and answer questions in class as well as through Slack!
We strongly encourage all students to form reading groups for joint study of the papers and the materials, to make the semester more fun and more productive.
Please feel free to reuse any of these course materials that you find of use in your own courses.
We ask that you retain any copyright notices, and include a written notice indicating the source of any materials you use.