What distinguishes multivariate analysis from univariate analysis?

Multivariate analysis is distinguished from univariate analysis primarily by its focus on multiple variables at once, as opposed to univariate analysis, which examines only a single variable. This capacity to analyze several variables simultaneously allows researchers to explore the relationships and interactions between these variables, providing a deeper understanding of the data.

In a multivariate context, analysts can assess how different factors might influence outcomes together, rather than in isolation, which is the limitation of univariate analysis. For example, in a business setting, one might look at how different price points, advertising spend, and customer demographics simultaneously affect sales figures, revealing insights that wouldn't be accessible through analysis of any single variable alone.

The other choices reflect misunderstandings about the nature of these analyses. Univariate analysis indeed focuses on one variable, not multiple, and it can incorporate both qualitative and quantitative data, which rules out the idea that multivariate analysis is limited to qualitative data. Additionally, multivariate analysis is often seen as more complex due to the intricate relationships it can reveal, rather than being less complex than univariate analysis.