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This session will address the advantages of box plots over bar charts for displaying the spread and variability in data.

Join our online workshop, where we'll unveil strategies for crafting the methods and results sections of your thesis.

This session covers density-based clustering approaches such as DBSCAN and related methods. We explore core concepts including density thresholds, reachability, and handling irregular cluster shapes and noise.

Do you want to learn how to use copyrighted material in your research, and how to protect your own rights as an author? If so, this workshop is for you!

This session will introduce participants to various types of t-tests, including one-sample, two-sample, paired, and one-sided tests.

This workshop introduces graph-based clustering, including community-detection approaches such as spectral clustering and modularity-based methods. We examine how similarity networks are constructed and how graph topology guides cluster formation.

Ever found it challenging to answer the critical “So what” question in your research? Struggle no more!

This session will introduce participants to non-parametric tests, which are useful when data distributions do not meet the assumptions of parametric tests.

Join our online workshop for a comprehensive overview of research proposal writing, applicable across various disciplines.

Whether you're gearing up for graduate school applications, navigating the academic realm, or preparing for the job market, this online workshop is your key to building a successful CV.

This session focuses on preparing mixed-type datasets—categorical, ordinal, and continuous variables—for clustering. We cover distance measures, data transformations, and quantification techniques that preserve variable meaning.

This session will introduce participants to the Analysis of Variance (ANOVA), a statistical method used for comparing the means of three or more groups.

This session will address the concepts of correlation, causation, and association in data. Participants will learn to differentiate between these concepts and to recognize and interpret various types of correlations.