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Home > Blog > Digital Marketing > Data Visualization >

What is Scatter Diagram? Definition, Types & How to create

Data rules the world — it’s everything, and it’s one of the primary reasons it’s used to communicate findings in any endeavor. To present such data in an easy-to-digest format, you would need charts or graphs — and that’s where scatter diagrams come into play. Here comes the big question — what is scatter diagram?

What is Scatter Diagram
What is Scatter DiagramWhat is Scatter Diagram

A scatter diagram is widely known as a correlation chart, scatter graph, or scatter plot. It’s one of the best tools used for determining the relationship between two variables. Ideally, one variable is plotted on the horizontal axis, while the other variable is plotted on the vertical axis.

The point of intersection pretty much shows the relationship pattern. Often, the scatter diagram is used to affirm or disprove the cause-and-effect relationship between two variables.

One of the primary objectives of a scatter diagram is to identify the relationship between two variables. Data set with over two variables will be somewhat difficult to study using a scatter diagram.

Still not sure of what a scatter plot is, and how to use it? Well, here is a better way of looking at it. Just keep reading you will find all answers and also will know about visualization library which helps to create this chart effortlessly.

Table of Content:

  1. What is scatter diagram?
  2. Types of scatter diagram
  3. Why should you use scatter plots and scatter analysis?
  4. Kind of Data That can be Represented on a Scatter Plot
  5. How to interpret data analysis on scatter chart?
  6. How to Create a scatter diagram?
  7. Pros of using scatter plot chart
  8. Cons of using scatter plot chart
  9. Scatter diagram — when not to use it
  10. Scatter diagram considerations

What is scatter diagram?

Definition: A scatter plot (or x-y graph) is a chart designed for expressing the relationship between two variables or data points. Here’s how it works…

Two data points are plotted along the x and y axes. The x-axis represents the independent variable, while the y axis represents the dependent variable. The rule is not set in stone as you can find both axes representing independent variables in some scatter plots.

But why do experts use the term scatter plot? Well, when data is plotted on these two axes, the resultant plot would be scattered. As a marketer, you can use scatter plots to analyze keywords data in SEM marketing.

Now you have a good grasp of what a scatter plot is, and why it is named scatter plot, here is why you should use scatter plots and scatter analysis.

Types of scatter diagram

What is scatter diagram? Well, you probably know the answer to the question by now. Beyond having a good grasp of what a scatter diagram is, you’ve got to know the various types of scatter diagrams.

The division of scatter diagrams is dependent on their correlation and slope type. When it comes to correlation, scatter diagrams are divided into three —

  • Strong correlation\ Positive Correlation
  • Moderate correlation\ Negative Correlation
  • No correlation\ No Correlation

What is Scatter DiagramWhat is Scatter Diagram

Scatter diagram with strong correlation

In this type of scatter plot, the data is marked as a dot, and the dependent variables are found on the y coordinate, while the independent variables are found on the x coordinate. By taking a close look at the graph, you would observe that the dots align in a linear pattern — and you can easily join them by drawing a straight line.

What is Scatter Diagram
What is Scatter DiagramWhat is Scatter Diagram

This arrangement denotes a strong relationship (or correlation) between the data. Experts choose to term it as scatter diagram with strong correlation (or high degree of correlation).

Scatter diagram with moderate correlation

Also known as a scatter diagram with a low degree of correlation — the data points are somewhat non-linear, and it’s pretty difficult to draw a straight line through it. Furthermore, the data points (marked as dots) are arranged close to one another.

What is Scatter Diagram
What is Scatter DiagramWhat is Scatter Diagram

Scatter diagram with no correlation

There is no degree of correlation or alignment in this type of scatter diagram. Most times, the data points are scattered all over the place, and it’s quite difficult to trace any form of relationship between them.

What is Scatter Diagram
What is Scatter DiagramWhat is Scatter Diagram

Why should you use scatter plots and scatter analysis?

  • Scatter analysis shows if there are any actual relationships between two variables or data sets. That is, it defines the relationship between two variables.
  • For each independent variable, there are multiple values of dependent variables.
  • There are pairs of numerical figures to help you pinpoint the value of each variable.

Kind of Data That can be Represented on a Scatter Plot

Generally, continuous data are represented on scatter analysis. Unlike discrete data where you get to have a pass/fail measurement, continuous data is used to measure an infinite set of data.

Some marketers prefer using continuous data on one axis of a scatter plot, while discrete data is used on the other axis. While using discrete data, you should quantify it by representing it with numbers (let’s say 1 – 10).

Scatter analysis is not all rosy — you would encounter some issues, and here are common issues you would likely encounter while using scatter plots.

By now, you probably have a good grasp of the big question — what is scatter diagram? and the kind of data represented on a scatter diagram. Here is how to interpret scatter analysis.

How to interpret data analysis on scatter chart?

There are trends in every market, and most times, statistical data are used in representing these trends — and that’s where scatterplots come into play. The problem lies in interpreting this data. Here is an easy way of interpreting scatter analysis.

A scatter plot is made of observations (or points), and each point has two coordinates. The first coordinate represents a piece of data — the data obtained by moving left or right, while the second coordinate represents the second piece of data. Typically, the second piece of data is found by moving up or down.

The first piece of data usually falls on the X coordinate, while the second piece of data usually falls on the Y coordinate. Ideally, a point (or dot) is placed at the intercession of these two coordinates, and the dot (or point) represents the observation.

Here’s something you need to know…

While interpreting a scatter plot, you can look for trends by moving from left to right. If there is an uphill pattern as you observe the trends from left to right, it implies a positive relationship between the two coordinates (X and Y coordinates). That is, as the value in the X-axis increases, the value in the Y-axis also increases.

If you observe a downhill pattern by moving from left to right, it implies a negative relationship between the X and Y coordinates. That is, as you move right, the X-value increases, while the Y-value decreases.

Finally, if there are no scatter diagram patterns (or relationships) between the coordinates, then there are zero relationships in the data observed.

Sometimes, you may observe a linear pattern in the data set, but it would not imply any type of dependency between the data set.

For instance, if a scatter plot of ad campaign spending is drawn, you would observe that marketers who spend much on ads tend to generate more results and make more profit. But that does not in any way indicate that shelling out many dollars in an ad campaign would yield profits.

It could be that marketers who spend more money on ad campaigns are more experienced, and as such, would likely write better ad copies and target the right audience.

You see, a linear relationship does not necessarily mean that one coordinate is entirely dependent on the other.

Next, you need to know the various types of scatter diagrams.

How to Create a scatter diagram?

ChartExpo is one of the advanced visualization tools that can help you create a scatter diagram.

Department Name Age Performance score Punctuality
Research and development Timothy 24 20 44
Research and development Richard 26 30 62
Research and development Michael 29 25 74
Research and development Paul 23 27 89
Research and development Bowles 38 32 96
Research and development Christopher 32 36 59
Research and development David 45 34 80
Research and development Joseph 22 42 50
Research and development Patrick 26 43 83
Research and development Pryor 40 47 82
Accounts and Finance Johnson 60 28 40
Accounts and Finance Colbert 55 60 75
Accounts and Finance Bowman 45 65 83
Accounts and Finance Francis 50 50 71
Accounts and Finance Collins 42 55 55
Accounts and Finance Jonathan 30 58 48
Accounts and Finance Eric 60 56 96
Accounts and Finance Pruden 29 82 75
Accounts and Finance Thompson 48 20 76
Accounts and Finance Frank 40 59 65
Sales and marketing Jerome 22 63 70
Sales and marketing Ronald 28 70 56
Sales and marketing Walker 30 75 87
Sales and marketing Guerrier 44 86 62
Sales and marketing Carlson 33 90 76
Sales and marketing Petersen 24 95 75
Sales and marketing Boyle 29 97 50
Sales and marketing Rendon 36 99 61
Sales and marketing Gomez 44 100 88
Sales and marketing Winship 27 50 59

Let’s say you’ve already got a data table, here is what you need to do.

If you have not downloaded this library yet, you can directly install ChartExpo Add-on for Google Sheets.

Once it is installed, you would have to navigate to the ChartExpo section on your Google Sheet Add-on by clicking on ChartExpo.

What is Scatter Diagram

Next, click on the create chart.

What is Scatter Diagram

Next, choose the scatter plot from the various options provided.

What is Scatter Diagram

Choose your desired metrics and dimension and click on the create chart button. Your chart would be displayed on your screen.

What is Scatter Diagram

Finally, you’ve got to track the relationship between the various variables.

What is Scatter Diagram
What is Scatter DiagramWhat is Scatter Diagram

Quadrants are representing different age group and there performance in their respective departments. Average line parallel to y axis is representing the average of age and average line parallel x axis is representing average of age. The size of the representing the punctuality of each individual. If you see how you can add title of chart, change colors of legends, and also can add trend lines for each department. Now, let start with how you can add title.

a. How to add title of chart:

What is Scatter Diagram

You can add title by clicking on Edit chart.

What is Scatter Diagram

Now, you have to click on highlighted pen and you can add title of chart as per your requirement.

b. How to change color of legends in chart:

What is Scatter Diagram

Click on highlighted pen and then go to Box from there you can choose color any of your choice. Using same method you can change colors of any other legend.

What is Scatter Diagram

Now, click on Save to save all changes.

c. For adding trend line:

You can show trend lines for department.

What is Scatter Diagram

He can do by clicking on Chart Setting on the right top of the window.

What is Scatter Diagram

Now, he will click on Trend Line. After that he will click Show button. From Polynomial Line, he can choose whichever degree line he wants. In this case, let’s suppose he wants 3rd degree trend line. After that he will click on Apply.

What is Scatter Diagram
What is Scatter DiagramWhat is Scatter Diagram

Different colors are representing different departments and the trend line is representing performance trend according to age of each department. E.g. Sales and marketing department trend is going upward to age 36 and slowly decline afterwards. These insights might be helpful for a company.

Moving on, here are things to have in mind before using a scatter diagram.

Application of scatter diagram

Here is some common application of scatter diagrams.

1. The Scatter diagram shows the relationship between two variables

Ideally, a scatter plot is used to show the relationship between two variables. It does not just show the relationship between variables, it also shows the nature of such a relationship.

The relationship could be linear or nonlinear, weak or strong, and positive or negative. Typically, the data points on the scatter plot represent the values of each data point. It also helps you to identify the overall pattern on the scatter diagram.

2. Shows correlational relationships

The Scatter diagram shows correlational relationships. Ideally, dependent variables are found on the vertical coordinates, while independent variables are found on the horizontal coordinates. This way, you get to easily identify the possible values on the vertical axis, provided the values on the horizontal axis are known.

3. Data pattern identification

The Scatter diagram shows patterns — it’s one of the core benefits of using it. Often, the grouping is dependent on the closeness of the values. This way, you get to easily identify any outlier.

Moving on, here are some interpretations of scatter diagram patterns you would likely observe in a scatter diagram.

  • If the marked dots (data points) slopes upwards, from the lower-left area of the plot to the upper-right area of the plot, then you’ve got a positive correlation — and that’s a rise.
  • If the marked dots (data points) slopes downwards, from the upper-left area of the plot to the lower-right area of the plot, then you’ve got a negative correlation — and that’s a fall.
  • Uncorrelated (or null) data is obtained when there is neither a positive or negative correlation between the data set.

Yes, everything sounds all fine and juicy, but a scatter diagram is not designed to be used every time. Here is when not to use a scatter diagram.

A quick recap here. You know the answer to the big question: what is scatter diagram, the benefits of using a scatter diagram, the kinds of data showcased on a scatter diagram, and the type of scatter diagrams.

But what are the pros and cons of using a scatter plot? Well, here is what you need to know.

Pros of using scatter plot chart

There are advantages to using each data visualization tool. For a scatter diagram, here are pros for using the tool.

  1. Scatter plots are one of the best tools for showcasing the correlation between large data sets.
  2. It helps to pinpoint the relationship between two data points (or variables).
  3. It’s a viable method for showing non-linear relationships in raw data.
  4. Zero technical skill is needed, and it’s pretty straightforward to plot and understand.
  5. You can readily identify the maximum and minimum points in a scatter diagram, and tracing the data range of flow is easy.
  6. Scatter diagram helps you to pinpoint the exact value in a data set.

Cons of using scatter plot chart

All is not rosy while using the scatter plot chart — here are the cons of using a scatter diagram.

  1. Scatter diagram is not ideal for showing the relationship of over two variables.
  2. It’s only recommended for data with numeric value.
  3. Sometimes, the relationship in the scatter diagram may be influenced by a third variable. Therefore, assuming that one variable is dependent on the other may be false and inaccurate.
  4. The more the scatter diagram shows a straight line, the stronger the relationship between the two variables.
  5. Sometimes, when the independent variable (x-axis) is varied widely, there will be no relationship in the scatter diagram.

Scatter diagram — when not to use it

A Scatter diagram offers an easy way of visualizing data, but that’s not to say it’s ideal for everything. Here are cases where it’s not ideal to use a Scatter diagram.

1. When there are numerous sets of data

When there is lots of data in your scatter diagram, you may end up clogging the entire graph area, and it could lead to overplotting.

Often the data points in the graph area become so dense, and ultimately form a large blob. It’s quite challenging to read up anything from such a scatter diagram.

As earlier stated, you can curb the issue of overplotting by merely using alternatives like a heatmap. A heatmap pretty much shows the densest area of your data set.

Furthermore, you could use various color codes to create translucent marked points — that’s a more reliable way of creating a heatmap-like effect for your analysis.

All in all, you should avoid using a scatter diagram when there are lots of data points. There is a high probability of forming a large blob when a scatter diagram is used.

2. When a point is not related

There are situations where you can predict that some data set is not related. In such situations, you’ve got to move on — no need of using a scatter diagram.

Why? Because there is no correlation, and a scatter diagram will do you no good. For instance, there would be no correlation for data of the weight of people in an area and the number of chairs in their homes.

Since the number of chairs in a home is not dependent on the weight of the person who owns the home, using a scatter diagram for such analysis would do you no good.

3. Avoid scatter diagram when there is more than one dependent variable

There are times when you can track a data set with more than one dependent variable. Often, it may be somewhat difficult to track such data sets.

If you desire to track a data set with more than one dependent variable, then you’ve got to change the color of each dependent variable. This way, you get to easily monitor each data point on the scatter diagram.

Scatter diagram considerations

Here are some things to note before creating a scatter diagram.

  • Regardless of the observed relationship in the scatter plot, do not assume that one variable is dependent on the other. A third variable could be the influencing factor.
  • When observing a scatter diagram, the more straight line the marked dots are, the stronger the relationship between the variables.
  • If the data is stratified, then there is a high possibility of zero relationship between the variables.
  • If a line is unclear, then you should check out if there is reasonable certainty of the existence of a relationship between the two variables. If there is no relationship (or correlation), then the pattern may have been a random occurrence.
  • If you observe no relationship in the scatter diagram, check if the independent variable covers a wide range. There are times when zero relationship implies that the data range is not wide enough.

FAQs:

What is a scatter plot chart?

A scatter plot is used for analyzing the relationship (or correlation) between two variables. With a scatter plot chart, you get to easily identify the relationship between two variables. Ideally, a variable is plotted on the Y-axis, while the other is plotted on the X-axis.

The intersecting point shows the relationship between the variables. In a scatter plot chart, one variable is plotted on the vertical axis, while the other variable is plotted on the horizontal axis.

What is the main purpose of a scatter plot?

The primary purpose of a scatter plot is to show the relationship between two variables. The marked dots show both the value of the data point and the overall pattern found on the data. Often, a scatter plot is used in identifying correlational relationships.

How to make a scatter plot in google sheets?

You can easily create a scatter plot in Google Sheets using ChartExpo Add-on.

Wrap Up

Whether you are a marketer or analyst, you would agree that it’s quite difficult to consume raw, unorganized data. But data visualization makes it pretty easy to convert data into something understandable and useful.

With a scatter diagram, you get to easily identify scatter diagram patterns and trends in any data. This way, you get to make more informed decisions. Also, a scatter diagram helps you see the big picture without missing a thing.

Your turn…

What is scatter diagram, and how would you use it in your next data analysis with ChartExpo?

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