Histograms display the shape of the distribution of continuous numeric data. The distribution can be symmetrical, right-skewed, left-skewed, unimodal, or multimodal? Knowing the shape of the distribution helps us decide which statistical test is appropriate. For example, if the distribution is symmetrical, we could use a t-test or linear regression. However, if the distribution is skewed, we’d need to use the Mann-Whitney test or median regression. Moreover, when the data has several peaks, we might need to transform the data before analyzing it. Otherwise, when we calculate central tendencies like the average, we will heavily misrepresent reality. Histograms also help to identify outliers, which is very useful for cleaning the data. So, visualizing the distribution with histograms and density plots helps us avoid these pitfalls.
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