The best way of visualizing similarity between data variables is by using statistical data analysis, which plays an integral role in stacking data points in a column format, thus creating a dot plot. Powerful data visualization guarantees a return on investment of $13.01 on every dollar that has been invested in the business.
Dot plots are popularly known as similarity matrices applied in both mathematical and statistical fields, especially when examining the similarities between univariate, continuous, and quantitative data. A dot plot chart is similar to a histogram graph, mainly used in processing small data sets existing in smaller groups.
Initially, a dot plot chart was hand-drawn before the invention of computers. The current version of a dot plot was invented by William S Cleaveland, who has been in the field for quite some time.
What is a Dot Plot?
A dot plot is an advanced statistical chart that incorporates data points on the vertical axis, which are illustrated in the form of marks similar to dots. In most cases, a dot plot comes in a shape similar to a histogram or a bar graph. This means that the height of every data set is equal to the number of items illustrated within the class intervals.
On some occasions, a dot plot is also known as a dot graph since it is a graphical data presentation that uses dots to present information. It is mainly used to showcase particular data trends in various fields across all the domains. When plotting a dot chart, you have to organize a group of data sets within the horizontal axis while the other on the vertical axis.
After organizing all your data values on the x and y axes, the corresponding data points of every pair of data values indicated are drawn while being directed towards the x-axis.
How to Interpret a Dot Plot Chart?
A dot plot chart is mainly used to showcase the distribution of particular data elements. When interpreting a dot plot, you need to consider variations, the shape of the distribution and the central tendency of the chart. Besides, you might opt to create a dot plot before or in conjunction with the given analysis to confirm the assumption of the chart.
When analyzing data on the chart, the tallest stacks within the graph represent the most common values available within your data set. Besides, this is precisely where most values tend to fail in the long run. On the other hand, the width of the distribution mainly indicates the total amount of variability within the displayed data.
When you realize a much broader distribution, keep in mind that it indicates a more significant variability. The only secret while reading a dot plot chart is to ensure that you know how to differentiate the chart variation and central tendency.
Types of Dot Plot Charts
Similar to any other type of data visualization tool, there are different types of dot plot charts that you need to know. Let’s check them out!
- Cleveland Dot Plot
William Cleveland invented this type of dot plot, which works similar to a scatterplot. The graph displays data vertically, displaying data in a single dimension. On other occasions, the Cleveland dot plot appears similar to a histogram since it uses a vertical one-dimensional data display.
Unlike a histogram that uses length to encode its data values, the Cleveland dot plot utilizes position to encode its data. Note that you don’t necessarily need to begin the data axis exactly at the origin when plotting a dot plot. This makes it easier for overlying multiple variables at the same time.
Even though a dot plot appears similar to a bar chart, the inventor of the chart stated that it is better to consider it a horizontal chart due to its functionality. When reading the data analyzed in a dot plot, you need to focus on the horizontal axis mainly.
- The Wilkinson Dot Plot
The Wilkinson dot plot was named after its inventor, Leland Wilkinson. What makes this type of dot chart distinct from the rest is that it utilizes a local displacement perpendicular to the scale, which prevents cases of the dots overlapping each other. Wilkinson established this chart type while working as a statistics professor.
Even though multiple dot plot variations were established in the past, Wilkinson was determined to develop a unique algorithm that could generate the chart using a computer software. This made it easier for the statistics professionals to generate excellent dot charts that can be easily readable.
Uses of the Dot Plot Chart
- Financial Institutions
Dot plots play a crucial role in the finance sector in displaying the interest rate projection for the finance committee meetings. Finance professionals can outline their dots across the graph to identify future interests within the sector. Also, it is used to determine the progress that has been achieved within the industry over a particular period.
- Bioinformatics
A dot plot chart in bioinformatics was introduced in 1970 by two professionals who were using the chart to visualize the similarities existing between a couples of nucleic acid sequences. The professionals used both the x and y axes to determine the similarities between the proteins.
According to a mathematical science study, identical proteins usually make a diagonal line from the dots outlined in a dot chart. Once the process is done, the respective dots are shaded to enhance visibility.
- Research
Research is a daunting task that needs one to be keen on various aspects to generate reliable findings. Suppose you are conducting research that involves uncovering similarities between different variables. In that case, a dot plot chart is the best option that you can use to uncover the data details. Once you have everything displayed, you can easily make an inference on the chart.
Also, you can use a dot plot to outline patterns and trends existing in your data after combining your research data. This will help you present highly actionable solutions used in decision making.
Conclusion
Dot plots offer an excellent model of visualizing the distribution of qualitative variables, since every dot represents a particular value. You can easily create the chart using Microsoft Excel or a dot plot maker, which has been programmed to execute the same. When you have values that have a frequency of more than one, the dots are stacked in a vertical format so that the collective height of the dots is the same as the frequency of the given value.
