There are hundreds of different types of graphs that a person can use to represent data. This often makes it difficult to figure out which type of graph is the optimal choice to display the information most clearly. Different graphs are good for different purposes, and in this post I will discuss a few of the key graph types that can be used in common situations.
If the data that is being displayed is not overly complex, then often times the simplest graphs are the best to use. The basic bar graph is good to use when comparing different numerical values against each other. For example, if data is gathered on several group’s opinions on a topic, a bar graph is an easy way to represent the number of people from each group that favor one opinion or the other. This kind of graph is also very useful in a financial standpoint, allowing for different dollar amounts to be compared between different time periods or companies. Another very simple yet powerful graph is the line graph. This graph is mainly used to represent trends, which clearly shows if a certain data set is increasing or decreasing based on the parameters. One of the most recognizable uses of this graph is in representations of the stock market. It shows the trends of different stock prices, and allows the reader of the graph to very quickly identify which stocks have an upward trajectory and which do not. Both bar graphs and line graphs can be understood without much analysis, making them very useful for quick and easy representations of data.
While bar graphs and line graphs are very useful in industries such as politics and business, they are not as widely used in the more scientific fields. The kind of data gathered through scientific research does not always make sense when put into these graphs. This is where graphs such as scatter plots are useful. The scatter plot allows two variables to be considered, and when the points are analyzed a relationship between these two variables can be found. This is helpful for scientists to find patterns in their data and make new discoveries based on connections that would not be able to be seen otherwise. Spider charts are also very useful in the scientific world, allowing for more than two variables to be considered for the data. A single entry can be considered against multiple variables around the circle of the graph, and additional entries can be compared in the same graph by having a color key present. This allows scientists to identify the entries that are best suited for a specific variable, and which are far below the competition.
While many graphs purpose are to display data in the most efficient manner, there are also times where the goal of a graph might be to be understood as simply as possible to a large group of people. These are graphs that may want to be used for presentations in a meeting for a large number of people so that the main idea can be communicated clearly. A very strong example of a graph in this category is the pictograph. This is a graph where the data gathered is translated into pictures so that it can be easily visualized by the audience. Venn diagrams are another graph that audiences easily understand. The venn diagram clearly shows two opposing sides, and shows the audience where the two intersect and where they have their differences. While these types of graphs are not necessarily the best for representing complex data, or even simple data, they can have a strong effect on an audience because of how easy they are to understand, and how they do not force the audience to analyze raw data too intensely.
There are many more kinds of graphs that can be used in a number of different situations. While some are hard to read, and some have very specific usage, there is a graph for every data set. This website shows a large number of different charts and graphs, many of which I have never seen before. New graph types will be created constantly with all of the new types and representations of data being introduced in the modern world, and it is important to keep all of these graphs in your arsenal when dealing with the unavoidable mountain of information in today’s age.
Nick Bagley
Information Science 