Which technique is used to visually represent the magnitude of values across two dimensions?

The heat map is indeed the correct choice for visually representing the magnitude of values across two dimensions. This technique employs colors in a matrix format to convey information about the values in a dataset, allowing users to quickly identify patterns, correlations, and areas of high or low intensity based on color gradients. Each cell in the heat map corresponds to the values of two variables, with the color representing the magnitude of a value, providing a useful visual summary of complex data.

In contrast, while bar charts and line graphs effectively display data trends and comparisons, they are typically limited to one-dimensional representations, showing either categories or values over time and missing the two-dimensional aspect of the heat map. Bubble charts, although capable of showing values across two dimensions with the size of bubbles representing a third variable, do not utilize color gradients to convey the magnitude as efficiently as a heat map does. Hence, the heat map stands out for its capability to visually summarize and facilitate an understanding of the relationships between two variables through color representation.