To compare two quantitative variables, the classic best choice (when available) is a scatter plot. In this version of the question, however, scatter plot is not one of the options. Among the given choices:

Bar graph – typically compares a categorical variable (categories on the x-axis) against a quantitative measure (bar height). It is not ideal for two purely quantitative variables.

Histogram – is designed to show the distribution of a single quantitative variable, not the relationship between two quantitative variables.

Pie chart – is used to show proportions of a whole and is not appropriate for comparing two quantitative variables directly.

Heat map (B) – can be used to display the relationship between two dimensions (which can be numeric) by using color intensity to encode the magnitude of a third variable or frequency of combinations. It is the best fit among the given choices for visualizing relationships across pairs of numeric values when a more suitable plot (like scatter) is not provided.

So, from the options listed here, Heat map (B) is the most appropriate to represent a relationship between two quantitative variables.

Note: In many CompTIA Data+ practice items that do include a scatter plot option, that is normally the correct choice for “two quantitative variables.” Here, with the restricted options, heat map is the best available match.

CompTIA Data+ Reference (concept alignment):

CompTIA Data+ Official Exam Objectives – Domain on Visualization (choosing appropriate visualizations for different data types).

CompTIA Data+ Official Study Guide – section distinguishing bar charts, histograms, pie charts, and heat maps, and their use cases.