How to Create a Scatter Plot in Excel with 2 Variables?

Scatter Plot is among the best-suited visualization designs for displaying causal relationships. Why?

The chart, as mentioned above, is amazingly easy to read and understand. Our brains can easily identify a trend using dots.

For instance, dots progressing in an upward-right side symbolize a linear (causal-effect) relationship. Therefore, learning how to create a Scatter Plot in Excel with 2 variables is a huge leap towards crafting compelling data stories.

Why stories?

You see, data with no narrative to simplify, is boring to any audience, including engineers perceived to be very analytical. If you want to lose your audience quicker than the rise and fall of a Ponzi scheme, talk about numbers.

Conversely, stories have an emotional appeal. Learning how to make easy-to-read and interpret charts, such as Scatter Plot, is an incredibly powerful addition to your data storytelling weapons.

However, it does have to be time-consuming or overwhelming, especially if you’re an ardent Excel user. The tool generates basic charts, which require additional time and effort to edit.

It turns out you can access ready-made and visually stunning Scatter Plot charts by installing a particular add-in into Excel.

In this blog, you’ll learn:

Table of Content:

1. Can You Create a Scatter Plot with Two Variables?
2. How to Create a Scatter Plot in Excel with 2 Variables?
3. When Should You Use a Scatter Plot With 2 Variables?
4. Wrap up

Can You Create a Scatter Plot with Two Variables?

Yes, it’s possible to generate a Scatter Plot with two variables. However, it depends highly on the tool you’re using for the task.

One of the most significant advantages of the chart is that you can quickly uncover hidden “cause-and-effect” relationships between two key variables in data.

Keep reading because we’ll cover how to create a Scatter Plot in Excel with 2 variables in the coming section.

How to Create a Scatter Plot in Excel with 2 Variables?

This section will use a Scatter Plot Chart to display insights into the tabular data below.

Cities	Products	Store Sales	Margin %
Dallas	Bread	21835	36
Dallas	Butter	7958	30
Dallas	Jelly	28031	40
Dallas	Pasta	30826	17
Dallas	Cheese	8522	24
Dallas	Ice Cream	55220	41
Dallas	Soda	37511	53
Dallas	Ketchup	11332	54
Dallas	Hand Lotion	43018	31
Dallas	Batteries	30559	50
Chicago	Bread	42919	38
Chicago	Butter	10756	39
Chicago	Jelly	37659	37
Chicago	Pasta	53742	53
Chicago	Cheese	21195	48
Chicago	Ice Cream	8934	59
Chicago	Soda	37851	60
Chicago	Ketchup	11994	41
Chicago	Hand Lotion	52606	24
Chicago	Batteries	11990	19
Boston	Bread	46077	47
Boston	Butter	46566	55
Boston	Jelly	25195	25
Boston	Pasta	59368	15
Boston	Cheese	57330	18
Boston	Ice Cream	27371	14
Boston	Soda	43569	13
Boston	Ketchup	34401	47
Boston	Hand Lotion	53559	10
Boston	Batteries	34039	16

Click this link to install ChartExpo into your Excel. Congratulations if you’ve installed the add-in into your spreadsheet.

To get started with ChartExpo, follow the simple steps below.

• Click the My Apps button to access the ChartExpo add-in.

• Select ChartExpo add-in and click the Insert button.

• Once the ChartExpo is loaded, you will see a list of charts.

• Then look for “Scatter Plot” in the list of charts, as shown below.

• Select the sheet holding your data and click the Create Chart from Selection button, as shown below.

• Check out your final chart below.

Insights

• There’s no clear relationship between sales and profit margin. It’s impossible to draw the line of best fit that connects the majority of the dots.
• The average profit margin is 35.13%.
• The average sales revenue is $35.1k.

How to create a Scatter Plot in Excel with 2 variables does not have to be time-intensive. Let’s visualize sample data using the chart above.

When Should You Use a Scatter Plot With 2 Variables?

Below are scenarios best-suited for a Scatter Plot Chart.

• Displaying hidden relationships between two variables

Scatter Charts are widely used to display the relationship between two variables. The relationships you can uncover using this visualization design are categorized as:

• Positive or negative
• Non-linear or linear
• Strong or weak.

The dots, which appear on Scatter Plot examples, represent the individual values of each of the key data points. More so, they allow you to extract trend insights from data faster.

• Identification of correlational relationships

You can use this insightful chart to uncover hidden correlational relationships that exist in your raw business data.

Interpreting Scatter Plot examples is incredibly easy.

The key to interpreting this chart is always to remember the following: independent variables (metrics) are found on the horizontal axis (x-axis). And the dependent variables are situated on the vertical axis (y-axis) in a Cartesian plane.

• Identification of data patterns

Use a Scatter Plot to identify the general trend of your key variables in your raw data.

Data points in this chart are grouped together based on how close their values are, which makes it easier to identify outliers. You don’t want to base your business decisions on outliers because they are outright misleading.

Interestingly, the nature of the correlations can also be estimated based on a specified confidence level.

• Positive correlation depicts an uptrend. Essentially, in a Scatter Plot with a positive correlation, data points slope upwards from the lower-left corner of the chart towards the upper-right.
• A negative correlation depicts a downtrend. Key data points slope downwards from the upper-left corner of the chart towards the lower-right.
• Data that are neither positively nor negatively correlated are considered uncorrelated (null).

FAQs:

Can you create a Scatter Plot with two variables?

Yes, it’s possible to generate a Scatter Plot with two variables. However, it depends highly on the tool you’re using for the task.

One of the chart’s biggest advantages is that you can easily uncover hidden “cause-and-effect” relationships between two key variables in data.

How can you explain the correlation between two variables?

Correlation is the statistical relationship between two variables in raw data. A correlation can be:

• Positive: Both variables move in the same direction.
• Negative: Growth in a variable causes a decline in the other one.
• No correlation: no coherent and reliable relationship between key data points.

Wrap Up

Scatter Plot is among the best-suited visualization designs for displaying causal relationships.

The chart mentioned above is straightforward to read and understand. Our brains can easily identify a trend using dots. For instance, dots progressing in an upward-right side symbolize a linear (causal-effect) relationship.

Learning how to create a Scatter Plot in Excel with 2 variables is a huge leap towards crafting compelling data stories.

Excel generates basic charts, which require additional time and effort to edit.

We recommend you install third-party apps, such as ChartExpo, in Excel to access ready-to-use Scatter Plot Charts.

ChartExpo is an add-in for Excel that’s loaded with insightful and easy-to-interpret Scatter Plots, plus over 50 more charts. You don’t need programming or coding skills to visualize your data using the Scatter Plot in ChartExpo.

How to create a Scatter Plot in Excel with 2 variables doesn’t have to be time-consuming or overwhelming, especially if you’re an ardent Excel user.

Sign up for a 7-day free trial today to access Scatter Plot Charts that are amazingly easy to interpret and visually appealing to your target audience.