What is a Scatter Plot? Learn how to make one!

You probably already know that within quality management there are some tools that help improve the production processes, right? Among these tools we have the Plot Diagram.

This tool has a great importance to overcome any problems in production, identifying the relationship between cause and defect of two quantitative variables. The tool considers variables that can be measured and counted.

You may be wondering what this diagram is. In this article, I will answer this question and still talk about its correlations, when to use it and also the main steps to put it together.

What is a Scatter Plot?

The Scatter Plot, also known as Scatter Diagram, is one of the tools that make up the quality.

How does Scatter Plot help us?

It is identified as a graph of vertical and horizontal axes, correlating cause and effect. Using these correlated data, it is possible to perceive in this Diagram whether there is a cause and effect relationship between the variables.

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What are the 5 types of correlations in Scatter Plot?

1. Positive Correlation

This type of correlation happens when there is a growing trend between the points. As one variable increases, the other variable also increases proportionally.

I will give an example for your better understanding: imagine applying more training hours within your production line. So what will be the result of this?

Considering the higher volume of training you offer, the higher is the quality of the product. We can say that quality is positively related to training.

2. Negative Correlation

This correlation is when they focus on a decreasing line. As one variable increases, the other decreases.

Still using the training example, we can see this relationship inversely proportional. The reduction of training hours, consequently will generate an increase in the hours of rework.

3. Perfect Correlation

It is identified as perfect when there is not a great dispersion between the points, the correlation will be total between the data, regardless of the trend, be it positive or negative.

4. Strong correlation

The lower the dispersion of points, greater the correlation between the data. With this, we can identify as strong when the data is very close, highly concentrated.

5. Weak correlation

You are sure to imagine that this correlation is inverse to the previous correlation. And, you are completely correct.

Then the greater the dispersion of points, the less the degree of correlation between the data. They have almost no correlation.

When to use the Scatter Plot?

Basically you use the Diagram to be able to check if the two variables are actually related and if there is any possibility of cause and effect relationship.

In addition, you can measure the level of intensity of the relationship between these two variables, whether it is strong or weak.

Now that you already know when to use it you may be curious how best to put this tool together.

This is what I'll be talking about in the next topic. I'll explain in a nutshell what are the 5 fundamental steps for building.

How to make a scatter plot step-by-step

STEP 1: First of all you need to determine and collect what data will be analyzed, to verify the relationship between them.

STEP 2:  In this step you already start to act. It is necessary to construct the vertical and horizontal axes of the graph. The causing variable is horizontally and the effect variable is vertically.

STEP 3: It is aimed to make the chart more complete, putting the complementary data, such as the names of these variables, the period of collection, etc.

STEP 4: With these data, and with the graph created, it is time to take the information data from the diagram.

STEP 5: We come to the last step, that is the analysis of these data, how they are related, always looking for the root cause of the problem.

How to make a scatter plot in Microsoft Excel

You can use Excel to help you make the scatter plot. After deciding which data will be analyzed, just create a column in the software with the data you want to use on the X column and another with the data you want to use on the Y column, as in the example below:

Then just select the two columns, go to the insert tab and search for the scatterplot.

Edit the plot as you wish using the “Chart Elements” button. In this case, for a better correlation analysis, the Trendline was added and for a better visualization the Gridlines were removed.

Realize through the trend line that there is a correlation between the order delivery time and the customer satisfaction note.

It's an important tool, but you have to be careful!

You have seen throughout this article on the importance of using the Scatter Plot in the productive environment. It seeks to relate and analyze the variables of cause and effect, always seeking to see what is wrong with the productive environment.

However, it is important to remember that this tool is a complex statistical method, and to use it it is necessary to have a minimum level of knowledge.

It requires an ability to actually implement this tool and take from it the results that are judged to be satisfactory to the company's claims.

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