To visualize the distribution of a continuous variable in ggplot2, which geometric layer should be used? (Select ALL the correct answers.)

Question

BlackTom AI · Accepted Answer

When visualizing the distribution of a continuous variable in ggplot2, you have a couple of primary geometric layers to choose from. 
Option 1: geom_histogram() — This layer creates a histogram, which bins the data and shows the frequency (or density) of observations within each bin, providing a clear view of the distribution shape, central tendency, and spread. It is a classic tool for distribution visualization. 
Option 2: geom_density() — This layer draws a smoothed density curve, giving an estimate of the data's distribution without binning, which can reveal the underlying shape more continuously and can be especially helpful with large datasets or when you want a smooth representation of the distribution. 
Both options are appropriate for depicting how a continuous variable is distributed. 
Why other possibilities (if considered) might be less suitable: if there were a option like geom_bar() for a continuous variable, it would typically summarize categorical data rather than distributions of a continuous variable, and thus would be inappropriate here. However, since the question allows multiple correct answers and both histogram and density are standard distribution visualizations for continuous data, they are both correct choices.

Data Science I Quiz #1

To visualize the distribution of a continuous variable in ggplot2, which geometric layer should be used? (Select ALL the correct answers.)

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