Univariate Bivariate Multivariate

Univariate analysis is all about looking at one variable on its own, with no comparisons, just understanding its distribution, central tendency, or spread. For example, I might look at the average test score in a class or the frequency of different grade ranges using histograms or summary statistics.

Bivariate analysis looks at the relationship between two variables, such as how students' study time affects their test scores. To analyze this, I'd use tools like correlation, scatter plots, or line graphs to identify trends or patterns.

Multivariate analysis, on the other hand, deals with three or more variables at once. It focuses on understanding how multiple factors combine to influence an outcome. For example, I might explore how sleep hours, study time, and caffeine intake together impact test scores. In that case, I'd use regression or a tree-based model to analyze the combined effect.