A scatter plot is a method of data representation using just dots. The major objective of the scatter Plot data is to represent the two variables X and Y and to find out whether the variables are related to each other or not.

The scatter plot chart helps you in identifying and establishing the linear relationship between two different variables. If the relationship is found between the two variables of the scatter plot chart, it is called a positive correlation, or else it is a negative correlation.

Positive correlation:

 If the line from X to Yorigin is continuously moving in the upward direction, in the ascending order, then it is a positive correlation. Let me give you an example for that: The sale of cold-drink increases as the heat in summer increases, so as the one variable increases, so does another.

Negative correlation:

 If the data is on a high point and starts coming downwards, in descending order, then it is a negative correlation. The perfect example of a negative correlation is the age of the car, and its price, which goes down as the car grows older. So as one variable decreases, so do the other.

The Scatter Plot chart is often created in Microsoft Excel, and it is very tough to function without it, especially if you want to represent any form of data. The Scatter Plot chart will help you find the relation between the two variables.

For example, if you want to find out whether coffee is affected by a change in climate from winters to summers, the Scatter Plot chart is the perfect data chart to help you find the answer to the question.

If the correlation will help how and when the sale of coffee is affected with the weather change.

How to construct a Scatter plot?

So, here are some of the tips that will help you construct a scatter chart:

  • Select Microsoft Excel and click on XY scatter chart, which you can find in the insert tab. You also have to choose a chart subtype that does not include lines.
  • Once the scatter chart represents data on the screen. If you find any problems in the chart, you can redo them.
  • Once it is done the right way, you can also add the trend line. You can do so by adding a chart menu button in the design tab.
  • When you are satisfied with the chart, and the design works for you, you are good to go.

Tips to plot data in Excel sheet

It is very important that you know how to create a scatter plot chart in an Excel sheet. It is very simple, follow these steps:

Enter the data

Youshould have data to begin with; if there is no data, you have to create newly recorded data for input into the software so that real work can be started.

Choose which graph option you want.

There is not one but so many graph options when it comes to Excel sheets, like bar graphs, pie charts, linear graphs, and much more. You should know which of the data presentation chart will work best for you.

Insert data variables

Once you have made a choice, insert all the data variables. You can also switch the data between X and Y with just a right-click on the graph.

Measurement options

If there is a need to increase or decrease the Y-axis, it can easily be changed to fit your likings.

Data re-order

If you want to change the data variables, highlight the data in the cell, click on the “data” option and click “sort” thus, the data is rearranged.

When to use a Scatter plot?

There are so many different usages of scatter plot charts. Here are some of them:

  • When trying to find the relationship between two variables.
  • When having paired numerical data.
  • When working with the root cause analysis tools to identify the potential for the problems.
  • When you want to visualize the correlation between 2 large datasets without regard to time.
  • Observation and reading of data become much easier.
  • It is the best method to show the non-linear pattern.

Common issues faced during using Scatter Plots


When there is a lot of data to put into the chart, there can be Overplotting. Overplotting is the case where the data starts to overlap to a point where there is difficulty seeing the relationship between points and variables. It can be very difficult to tell how densely packed data points are when many of them are in a small area.

However, here is a trick to get rid of this issue. You can subset the sample data points, and that will give you the idea of correlation. Apart from that, you can also change the form of dots adding transparency to allow for overlaps to be visible, it will reduce the point size, and fewer overlaps will occur.

Interpreting correlation as causation:

This is more of an issue with interpretation. Simply because we observe a relationship between the two variables in a scatter plot, it does not mean that changes in one variable are responsible for changes in the other. This gives rise to a common phrase in statics that correlation does not imply causation.

 So in order to establish the causal link, further analysis to control or account for other potential variables effects needs to be performed that will rule out any other possible explanations.


Trust me; scatter Plot chart is so easy to use. It is one of the best ways for data representation. So, if you, too, find it hard to deal with reporting tasks in Microsoft sheets, then you should try a hand a Scatter Plot chart. It will help you understand the correlation between the two sets of data better.

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