Dot plot frequently asked questions

What is a dot plot?

A dot plot is a simple graphical representation of data where each data point is shown as a dot above a number line. It is used to show the distribution of data points and to compare frequencies of specific values in a dataset.

When should I use a dot plot?

Dot plots are useful when:

• You have small to moderate datasets.
• You want to visually identify clusters, gaps, or patterns in the data.
• The data is discrete (e.g., counts, ratings, or categories).

What type of data works best for a dot plot?

Dot plots are most effective for:

• Discrete data (e.g., count data, survey responses, etc.).
• Small to medium-sized datasets (as it can become cluttered with too many points).

Can I use dot plots for continuous data?

While dot plots are typically used for discrete data, they can also be adapted for continuous data by rounding values to discrete intervals or by using different colors or sizes of dots to represent frequency ranges.

How do I interpret a dot plot?

Cluster of dots: Indicates a concentration of data points at a specific value.

Gaps in the plot: Suggests a lack of data points within a certain range.

Single dots: Represent individual data points.

How is a dot plot different from a bar graph?

Dot Plot: Each data point is represented by a single dot on a number line, making it easier to see individual values.

Bar Graph: Data points are grouped into categories and displayed as bars, which represent frequencies or counts for each category.

What are the advantages of a dot plot?

Simple to Create: Dot plots are easy to draw by hand or create digitally.

Clear Visualization: They show individual data points, making it easy to see specific values and their frequencies.

Effective for Small Datasets: Dot plots are especially useful for small datasets where other plots (e.g., histograms) might be overkill.

What are the different types of dot plots we can create?

Let's take an example of a manufacturing process that makes bolts. Two machine tools, Machine 1 and Machine 2, manufacture these bolts. The diameter of the bolt is a critical tolerance that needs to be controlled. These machines run for two shifts daily (Shift 1 and Shift 2) by different operators. The following 1000 rows of data were collected for this process:

Shift	Machine 1	Machine 2
1	1.512637086	1.461893716
1	1.514703275	1.499922138
1	1.536790136	1.454054748
1	1.509811708	1.502964807
1	1.527360168	1.538022745
1	1.517283088	1.358204676

We want to depict the diameters using the Dot plots graphically. The following types of box plots can be created:

1. Dot plot of diameter for all bolts created on Machine 1
   
2. Dot plot of diameters of bolts comparing Machine 1 and Machine 2 shown on same plot
   
3. Dot plot of diameters of bolts comparing Machine 1 and Machine 2 shown on different plots

Note that we can have up to 20 categorical variables for this plot. If you have more than 20 categorical variables, you must split the data into multiple groups and create a box plot for each group. You can use the by-variable option for this exercise.

Case 1: Dot plot of diameters for machine 1.

For this case, click on Analysis Setup and specify the Data options as shown below:

The graphical output is shown below.

Case 2: Comparison of bolt diameters across Machine 1 and Machine 2 shown on the same plot

For this case, click on Analysis Setup and specify the Data options as shown below:

The graphical output is shown below.

Case 3: Comparison of bolt diameters of Machine 1 and Machine 2 shown on different plots

For this case, click on Analysis Setup and specify the Data options as shown below:

The graphical output is shown below.

When do we use dot plots vs. histogram?

We usually use dot plots when the number of data points is less than 50. If we have more than 50 data points, we use the histogram. In a dot plot, each data point is shown as a dot, while in a histogram, the individual data points are not shown but are grouped as a bar.

Below is an example of a data set that has 1000 points that has been plotted using both the dot plot and histogram.

Below is a comparison of the two plots when we have only 10 data points.

Note that bin sizes are different for both dot plots and histograms, so the Y-axis count values are different in each bin.

How do we add a horizontal reference line on the dot plot?

To add a horizontal reference line on a chart, click on Analysis Setup > Charts and specify the value in the Horizontal Ref Lines as shown below:

The resulting chart will have a reference line added to the chart, as shown below:

You can specify multiple values separated by a semi-colon if you need more than one horizontal line.

Are bins used for creating the dot plot?

Yes, the data is placed into bins before creating the dot plot. You can control the number of bins or leave it at Auto and let the system pick a bin size for you. To adjust the bins, click on Analysis Setup > Setup > Bins and pick a value for the number of bins.

What is stacking groups in a dot plot?

If there is a single group or if multiple groups are plotted on different charts, then stacking groups has no effect. This option is only used when multiple groups are plotted on the same chart. Click on Analysis Setup > Setup > Stack Groups and set the desired option.

The comparison of the dot plots without and with grouping is shown below:

Note that in the first case, each dot plot is created on the horizontal x-axis starting at 0. In the second case, once the first group is created, the second group using that as a starting point and then creates the dot plot. If the data for your exercise is cumulative, then you can use the stacking option to create the dot plots.

What is the difference between a dot plot and a scatter plot?

Dot Plot: Used for small datasets with discrete data points, usually plotted on a number line.

Scatter Plot: Typically used for larger datasets with continuous data. Points are plotted on both the x- and y-axes to show relationships between two variables.

Are there any limitations to using a dot plot?

Not Ideal for Large Datasets: For large datasets, dot plots can become cluttered and difficult to interpret.

Limited to Discrete Data: Dot plots are best for discrete data and may not work well for continuous data.

Can be Time-Consuming: If you have a large number of unique values, it can take time to plot each dot.

Can dot plots show the frequency of data?

Yes, by stacking dots for repeated values, dot plots can show how often certain values appear in a dataset, effectively representing frequencies.

 Reference: Some of the text in this article has been generated using AI tools such as ChatGPT and edited for content and accuracy.

 

 

 

 

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