If you’re looking for a step-by-step tutorial on how to make a scatter plot in Google Sheets, your search ends here. Whether you’re just starting your data visualization journey or you’re a seasoned spreadsheet user looking to expand your skills, this guide will help you create scatter plots for data analysis, from beginner to advanced.
Scatter plots are valuable tools in the world of data visualization. Essentially, they allow you to uncover patterns, correlations, and outliers within your datasets.
In this blog post, we’ll show you what scatter plots are by exploring their advantages and delving into their essential features.
In addition, we’ll walk you through the process of creating eye-catching scatter plots.
What are scatter plots?
In data visualization, scatter plots stand out as powerful tools for representing the relationship between two variables. Also known as a scatter diagram, a scatter plot displays individual data points on a two-dimensional graph, with each point representing the values of two different variables. The positioning of these points provides a visual representation of how the variables interact with each other.
In Google Sheets, creating a scatter plot is a straightforward process that brings your data to life. By utilizing the built-in chart tools, you can transform raw data into a visually compelling scatter plot.
This dynamic representation allows you to discern patterns, trends, and correlations within your dataset. Whether you’re analyzing sales figures over time or exploring the correlation between marketing spend and customer acquisition, scatter plots offer a clear and intuitive way to grasp the relationships in your data.
What are the advantages of using scatter plots?
Scatter plots offer a variety of advantages that make them a useful tool for data analysis and decision-making:
Visualizing relationships: one of the primary strengths of scatter plots is their ability to visually depict the relationship between two variables. Whether the relationship is linear, nonlinear, positive or negative, a quick glance at a scatter plot can provide valuable insights.
Identifying trends and patterns: scatter plots are great at revealing trends and patterns within data. By examining the distribution of data points, you can quickly identify clusters, outliers, or trends.
Correlation assessment: scatter plots are invaluable for assessing the correlation between two variables. The clustering or dispersion of data points on the graph provides a visual indicator of the strength and direction of the relationship.
Outlier detection: outliers, or data points that deviate significantly from the general pattern, can have a substantial impact on the interpretation of your data. Essentially, scatter plots make it easy to identify and analyze outliers, helping you understand their impact on your dataset.
Key features of scatter plots
To effectively leverage scatter plots in Google Sheets, it’s essential to understand their key features:
Data Points: individual points on the graph represent specific values of the two variables you are comparing.
X and Y-Axis: the x-axis (horizontal) and y-axis (vertical) represent the two variables being compared. Each axis provides a scale for measurement.
Trendline: a trendline can be added to the scatter plot to help visualize the overall trend or relationship between the variables.
Labels and titles: clear labels and titles are crucial for conveying the meaning of the scatter plot.
Color and markers: using different colors and markers for data points can enhance the visual clarity of the scatter plot. This makes it easier to differentiate between groups or categories.
Gridlines: by providing a reference for the viewer to understand the scale of the variables, gridlines on the graph help readers interpret values accurately.
By harnessing these features, you can transform your scatter plot from a simple chart into a powerful tool for extracting meaningful insights from your data. In the next section, we will guide you through the step-by-step process of creating a scatter plot in Google Sheets.
How to make a scatter plot in Google Sheets
Now that you know the advantages of using scatter plots and their key features, let’s learn how to make a scatter plot in Google Sheets.
In this example, we’ll use a spreadsheet that contains the CTR (Clickthrough Rate) and the CPA (Cost Per Acquisition) of a lead generation campaign. Before we create the scatter plot, let’s take a quick look at what CTR and CPA stand for.
In marketing, Clickthrough Rate (CTR) is a metric that measures the percentage of people who click on a link compared to the number of people who have viewed the ad. If 100 people see an ad but only 2 click on it, the CTR is 2%.
In contrast, Cost Per Acquisition (CPA) is a metric that measures the average amount of money spent to acquire a customer or lead through a specific marketing campaign.
Theoretically, the higher the CTR is, the lower the CPA tends to be.
Let’s make a scatter plot to establish a correlation between the CTR and the CPA. Click Insert and select Chart.
Under Chart type, select Scatter chart. Then add the X-axis (CTR) and the series (CPA).
Customize your chart
After creating the scatter chart, we can customize it to our liking. First, I’ll change the background color.
Now I’ll add a title, select a font and change the text color.
When I click on Series, I can edit the markers and customize the color.
By adding a trendline, you can help readers visualize the overall trend or relationship between the variables.
If you add gridlines and ticks, your audience will be able to read the data from the chart more easily.
As you can see, there’s correlation between the CTR and the CPA. A higher CTR usually indicates that the ad is attracting more clicks, which might lead to a higher conversion rate and consequently a lower CPA.
By creating a scatter plot, we can identify trends and outliers. When you look at the chart, it’s easy to find an outlier. One day, the CPA went through the roof and almost reached $9.50.
There you have it! We have just built a scatter plot to help us visualize the relationship between two variables.
If you want to create a pie chart instead, check out this article on how to make a pie chart in Google Sheets.