IBM Data Science Practice Test

A network graph is best suited for which type of data?

1. Geographic distribution

2. Categorized data

3. Time-based data

4. Multi-dimension data

The correct answer is: Multi-dimension data

A network graph is particularly effective for representing multi-dimensional data because it allows for the visualization of complex relationships and interactions between different entities or nodes. In a network graph, each node represents an individual data point, and the edges (or connections) between nodes convey the relationships among them. This structure makes it easy to visualize not just individual data points, but also how they interconnect across various dimensions, such as attributes or categories. This capability is pivotal in scenarios like social network analysis, where individuals can have multiple relationships and attributes that intersect in various ways. By using a network graph, one can effectively demonstrate the complexity of these relationships, capturing the nuances that multi-dimensional data presents. While geographic distribution, categorized data, and time-based data have their respective visualizations, such as maps, bar charts, or line graphs, they do not inherently capture the relational aspects between multiple dimensions as proficiently as a network graph does. Thus, for illustrating complex, interconnected data, the network graph serves as a superior tool.