Which analysis typically focuses on the relationship between only two variables?

Bivariate analysis is designed specifically to examine the relationship between two variables. This type of analysis helps analysts understand how changes in one variable may influence changes in another. Common techniques in bivariate analysis include correlation and regression analysis, where an analyst can determine the strength and nature of the relationship (positive, negative, or none) between the two variables in question.

Multivariate analysis involves three or more variables and is geared towards understanding complex relationships and interactions among them, which is more extensive than what bivariate analysis focuses on.

Univariate analysis, on the other hand, examines a single variable on its own, providing insights into its distribution, central tendency, and variability without considering relationships with any other variables.

Cross-sectional analysis refers to observations made at a single point in time, which can include analyzing two variables but does not inherently focus on their relationship specifically as bivariate analysis does. Therefore, the focus on just two variables makes bivariate analysis the correct choice for understanding their direct relationship.