What does multivariate analysis in data analytics examine?

Multivariate analysis is a statistical technique used to understand the relationships between two or more variables simultaneously. This approach is particularly beneficial in data analytics because many real-world scenarios involve multiple factors that can influence outcomes. For example, in a marketing analysis, a data analyst might look at how variables such as age, income, and shopping behavior interact with one another to influence purchasing decisions.

By examining multiple variables together, analysts can identify patterns, correlations, and possible causal relationships that may not be apparent when looking at each variable in isolation. This comprehensive view enables more sophisticated models and insights, leading to better decision-making, predictions, and interpretations of data.

In contrast, focusing solely on the average of multiple datasets, analyzing only two variables at a time, or looking at the correlation of a single variable over time does not capture the complexity of interactions among multiple variables, which is the hallmark of multivariate analysis.