Graphing Data: Reasons and Methods

Updated on: March 1, 2023

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Table of Contents
  1. Introduction
  2. Definition and Purposes of Graphs
  3. Line Graphs
  4. Elements of a Simple Line Graph
  5. Transferring Data to a Graph
  6. Additional Graphing Conventions
  7. Cumulative Graphs
  8. Bar Graphs
  9. Conclusion


The goal of this paper is to demonstrate the awareness of the chapter about data collection methods. Data collection is an important step any researcher should take, and several approaches exist to store information. Graphing data is one of the possible methods to communicate information visually. Graphs may be simple lines, cumulative, and bar, and the choice of transferring processes usually depends on the type of information. This paper is organized to explain the basics of graphs and their purposes. In addition, the elements of line graphs and peculiarities of other graphs will be discussed to be ready to work with different amounts of information.

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Definition and Purposes of Graphs

Graphs are critical elements of any data collection and analysis process. Researchers use them to arrange information and make it clear to the reader. In most cases, all graphs are simple and uncluttered to make sure that a person understands the main idea. It is expected to present the progress of information in a graph, and the boundaries of an intervention or some instructions are properly identified.

Graphs may serve many purposes, and some of them is to present a means for organizing information. Sometimes, it is hard to interpret the amounts of information, and graphs contain a picture with several numbers and explanations. Second, graphs promote formative evaluation to demonstrate if a procedure or performance works well. Finally, graphs support communication between a reader and a performer.

Line Graphs

Among a variety of graphs, students are encouraged to use simple line graphs because of several reasons. First, such graphs save information in an effective serial manner. As a result, researchers are able to monitor information about the intervention. In most cases, such graphs are planned in special graph papers or with the help of computer programs. Modern students can use different computer software and find instructional help online. Some general requirements include proper alignment (as per instructions) and equal intervals that depend on the chosen style. The purpose of simple line graphs is to organize regular monitoring and evaluation of the events. Still, grids are usually not allowed in formal publications to make reading easy and comfortable.

Elements of a Simple Line Graph

To be ready to create a simple line graph in a proper way, a person should know about its major elements. In this chapter, the authors focus on three aspects of graphs axes, data, and the representation of personal information. Axes are the boundaries of graphs, and each graph usually has two axes. The abscissa is the horizontal axis, also known as the “x” axis, and the ordinate is the vertical axis, also known as the “y” axis. There is an abscissa ratio to be considered while drawing the lines that is 2:3, meaning that if x=2 inches, then y should be 3 inches. Data points represent the occurrence in the form of small circles or triangles. Data paths are lines that connect points on a graph. Finally, the creators of graphs should identify themselves in the bottom right corner.

Transferring Data to a Graph

Researchers should use different transferring methods, depending on the type of information that must be presented. For example, permanent product data includes items/percentage of items that result from behavior. Event data is based on the number of occurrences of behavior under the condition that time is consistent. Rate data explains fluency of performance and makes it possible to share judgments. If a researcher is concerned about the speed and accuracy of the information, they choose rate graphs.

Interval and time sampling data contains the numbers of percent of total intervals that are necessary to observe the behavior under analysis (usually called percentages). Depending on the required periods of time for a researcher to complete a task, duration data may be transferred to a graph as the number of hours, minutes, or seconds. In other words, duration is a period that is necessary to finish an assignment, meeting all the necessary requirements and following the entire format. Finally, latency data can be transferred to a graph under specific rules. This type of data is similar to the previous one, with the only difference being the nature of the time period. In this case, hours, minutes, or seconds should be checked before a task is initiated (before the occurrence).

Additional Graphing Conventions

In the chosen chapter, one of the goals is to get the reader prepared for learning new material. Thus, some additional graphical conventions and complex graphs are mentioned. For example, an intervention in a graph is a strategy that a presenter uses to change (decrease) his or her behavior. There are certain phases in each intervention, known as conditions when different approaches are introduced. To observe changes in a scheme, any graph should have baseline data or the current level of behavior. Dash lines help to separate conditions or behaviors, and dash points are not connected between conditions. Presenters are free to use these additional conventions per their needs, but several simple rules cannot be neglected.

Cumulative Graphs

There are situations where it is enough to describe intersections despite the level of performance, and simple line graphs are enough to complete this task. Still, when the number of occurrences in a session should be identified, cumulative graphs are preferred. To create such graphs, the number of occurrences from previous sessions is also included. Following these rules, cumulative graphs allow the creation of an additive view of information across several sessions at the same time. An upward curve is a common form of a cumulative graph, and the sum of all responses is taken into consideration to gather the material for a graph.

Bar Graphs

In addition to simple line graphs and cumulative graphs, bar graphs are commonly used in research. This method of data presentation is also known as a histogram. It consists of two axes, one abscissa (that represents a session) and one ordinate (that represents performance). Compared to previous graphs where data points help to organize information, histograms contain vertical bars, which help display data with more precise interpretation and cover a large observation period. Finally, when several data paths should be represented, it is hard to use one simple line. Therefore, the evident pros of a bar graph are the possibility to summarize performance across several periods of time or by several participants.


In general, despite the fact that this chapter focuses on the discussion of one method for graphing data, several brief notes and explanations contribute to a better understanding of an entire process. There are many reasons for making a decision to graph data, and those who prefer this method gain a number of benefits like simple performance, time-saving, and the introduction of multiple items within one graph. In this chapter, attention was paid to simple line graphs, cumulative graphs, and bar graphs. In addition, six examples of how to transfer data depending on its type were described. Finally, regardless of the level of readiness to work with graphs and the quality of information, compute software remains the main source to create graphs quickly and effectively.

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