how to draw a scatter diagram, plot, graph with examples what is a scatter diagram with correlation

What is a Scatter Diagram ? – A Scatter Diagram is also known as Scatter Plot or Graph is one of the seven basic tools of quality like Pareto Chart or Control chart. Simply put, it is a kind of mathematical graph which shows values of commonly two variables for a group of numerical data. Horizontal and vertical axis are used to determine the position of each variable of the data set. The points will form a line shape if the variables are correlated. Some PMP (Project Management Professional) aspirants find it difficult to understand because other charts use lines or bars to demonstrate data sets, while a scatter diagram uses only points to show correlation. On the other hand, the scatter plot is very easy to understand like the other charts and graphs. In this article, we will answer: What are the Scatter diagrams used for? and How to Draw a Scatter Diagram? with a Scatter Diagram Example.

What is a Scatter Diagram?



There are seven basic quality management tools for planning, monitoring and controlling processes to improve the quality-related issues within the organization. Scatter Diagram is one of them.

A scatter graph is a type of diagram which demonstrates the relationship between two variables for a group of numerical data. In quality management, it is used to show the relationship between an element of a process on one axis and the quality defect on the other axis.

How to Draw a Scatter Diagram?

The scatter diagram is created with two variables, usually, the first variable is under the control of the researcher and the second variable depends on the first one. The independent variables which affect the dependent ones are typically plotted along the horizontal axis (X-axis) and the dependent variables are plotted along the vertical axis (Y-axis).

Independent & Dependent Variables
Independent & Dependent Variables

The independent variable affects the dependent variable, therefore, the independent variable is also known as the control parameter.

Sometimes both variables may be independent. In that case, the scatter graph demonstrates the level of correlation between them. In other words, it helps to determine how closely the variables are related.

What are the Scatter Diagrams Used For?

They are used to determine the relationship between two variables. In other words, you use the scatter plots to demonstrate how two variables are correlated.

Scatter Diagram Example

Let’s review the example to understand the subject better.

An HSE manager collects data for the two variables below in order to understand the relationship between the number of accidents and long working hours within a construction project.

  • Number of Accidents
  • Working Hours

The HSE manager plots the data in a scatter plot by assigning the “working hours” to the horizontal axis (X-axis) and the “number of accidents” to the vertical axis (Y-axis).

The scatter graph of all the data in the research helps the HSE manager to understand the relationship between the two variables. He notices that as the working hours’ increases, the number of accidents also increase. “Working hours” is the independent data and the number of accidents depends on the working hours.

Below table shows the working hours and accidents within a project.

Working Hours vs Accidents

Working HoursAccidents 
1100011
1200017
1300024
1400031
1500040
1600047
1700057
1800066
1900080

 

Below is the same data as a Scatter Plot.

Scatter
Scatter Diagram Example

Correlation

Correlation is used to define the relationships between the variables. In other words, correlation shows how the variables relate to each other. Scatter diagrams can be categorized according to the slope of the data points. Three types of correlation: positive, negative, and none (no correlation) may be shown in the diagrams based on the data set and variables.

Scatter Diagram with No Correlation



If there is no possible relationship between the variables, the correlation type is be called “no correlation”. Also, it can be named as zero correlation type. The two variables are not linked. In that case, you cannot draw any line through them. For example, air temperature and shoe size have no correlation; as the air temperature increases, shoe size is not affected.

Scatter Graph No Correlation Example
No Correlation

Scatter Diagram with Negative Correlation

In this type of correlation one variable increases as the other variable decreases. For example, if the speed increases, travel time to a destination decrease.

Negative Correlation Example
Negative Correlation

Scatter Diagram with Positive Correlation

If there is a positive correlation between the variables, this means that if one variable increases the other one increases and if one of them decreases the other one decreases.  For example as the speed of a turbine increases, the amount of electricity that is generated increases.

 

Scatter Diagram Positive Correlation Example
Positive Correlation

Strong and Weak Correlation



If the variables are a bit closer to each other, this means that there is a weak correlation between them. It can also be called “Scatter Diagram with Low Degree of Correlation”. If the variables are closer to each other, this means that there is a strong (high degree of) correlation between the variables.

Conclusion

Scatter diagrams are used to understand the relationships between variables. They are very easy to create and use. If the data don’t cover a wide enough range, the relationship between the variables is not apparent. In some cases, both of the two variables may be affected by a third variable. Some PMP aspirants confuse the fishbone (Ishikawa ) diagram with the scatter plot. The fishbone diagram enables to define the root cause of a problem where the scatter plot helps to look for a relationship between variables. If you want to share your experiences regarding how to draw a Scatter Diagram, you can use the comments section.

External References

[1]: ASQ: The Global Voice of Quality

See Also

Fishbone Diagram

Accuracy vs Precision

Pareto Chart

Cost Benefit Analysis Example

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