How to interpret a relative frequency histogram?

A relative frequency histogram shows the proportion of data in each category.

To interpret a relative frequency histogram, first identify the categories on the x-axis and the relative frequencies on the y-axis. The height of each bar represents the proportion of data in that category. The total area of the bars should add up to 1.

For example, consider a relative frequency histogram of the heights of a group of people. The x-axis may be labelled in intervals of 5cm, and the y-axis may be labelled in intervals of 0.1. The height of each bar represents the proportion of people with heights in that interval.

To analyse the data, look for patterns in the histogram. Are there any peaks or clusters? Is the data skewed to one side? Are there any outliers? These observations can provide insight into the underlying distribution of the data.

It is also important to consider the sample size and any biases in the data collection. A small sample size may not be representative of the population, and biased data may lead to inaccurate conclusions.

In summary, a relative frequency histogram is a useful tool for visualising and interpreting data. By identifying patterns and considering sample size and biases, we can gain insight into the underlying distribution of the data.