IBM Data Science Practice Test

When would you use a histogram?

1. To help an analyst compare groups

2. To understand the distribution of a variable

3. To understand trends over time

4. When working with historical data

The correct answer is: To understand the distribution of a variable

A histogram is primarily used to understand the distribution of a variable. It visually represents the frequency of different values in a dataset, allowing you to see how the data is spread across different ranges or bins. By displaying the data in this manner, you can identify key characteristics such as the shape of the distribution (normal, skewed, bimodal, etc.), the presence of outliers, and the central tendency (like the mean or median). This capability makes histograms particularly valuable in exploratory data analysis, where gaining insights into the underlying patterns of data is crucial. The information obtained from a histogram can guide further analysis or model selection by revealing whether the assumptions of certain statistical methods are met. In contrast, while comparing groups, understanding trends over time, or working with historical data can benefit from data visualization, these aspects are not the primary focus of a histogram. Other graphical tools such as box plots, line graphs, or bar charts would be more appropriate for those purposes. Therefore, using a histogram is singularly focused on analyzing the distribution of a variable, which is why it is the correct choice in this context.