How to interpret a histogram?

A histogram is a graphical representation of data that shows the frequency distribution of a set of continuous or discrete data.

Histograms are used to display the distribution of a dataset. The x-axis represents the range of values in the dataset, while the y-axis represents the frequency of occurrence of each value. The bars in a histogram are usually adjacent to each other, with no gaps between them, to indicate that the data is continuous.

To interpret a histogram, you need to look at the shape of the distribution. A histogram can be symmetrical, skewed to the left or right, or bimodal. A symmetrical histogram has a bell-shaped curve, with the mean, median, and mode all being the same value. A skewed histogram has a longer tail on one side, indicating that the data is not evenly distributed. A bimodal histogram has two peaks, indicating that the data has two distinct modes.

You can also use a histogram to identify outliers in a dataset. Outliers are values that are significantly different from the rest of the data. They can be identified as values that fall outside the range of the majority of the data.

In summary, a histogram is a useful tool for visualising the distribution of a dataset. By analysing the shape of the histogram, you can gain insights into the characteristics of the data, such as its symmetry, skewness, or bimodality. You can also use a histogram to identify outliers in the data.