How to Use a Scatter Plot Maker to Visualize Data?

Let’s imagine you want to establish whether there’s a correlation between current inflation and global fuel prices.

What’s your go-to chart for the task?

A Scatter Plot Chart is one of the graphs we recommend in this scenario. Why?

The chart is best-suited for displaying causal relationships between data points. More so, it’s straightforward to read and understand. Remember, we can identify a pattern using dots.

Learning how to use a Scatter Plot maker is a massive leap toward analyzing your data for correlation insights. So, it does not have to be time-consuming or overwhelming, especially if you’re an ardent Excel user. And this is because the application lacks ready-made Scatter Plot Charts.

So?

To transform Excel into a reliable Scatter Plot Maker, install a third-party add-in (which we’ll talk about momentarily).

In this blog, you’ll learn:

• How to get started with a Scatter Plot Maker?
• What is a Scatter Plot?
• When should you use a Scatter Plot maker?
• Importance of using a Scatter Plot generator for data analysis
• Advantages of a Scatter Diagram.
• How to create a Scatter Plot?
• We’ll recommend the proven add-in to install to access ready-to-go Scatter Charts in Excel.

Before delving right into a how-to guide, we’ll address the following question: what is a Scatter Plot?

What is a Scatter Plot?

Definition: Scatter Plot Chart is a visualization design you can use to display relationships between variables in data.

Each axis in the chart represents a metric understudy. Plotting data points along Scatter Plot’s two axes can help you uncover hidden relationships.

Check out an example of a Scatter Plot.

Let’s imagine you want to establish the relationship between ice cream sales and the average temperature of the hour.

One variable will represent ice cream sales, and the other will depict hourly average temperatures. As you plot your data, you’ll notice how the hourly temperatures affect the ice cream sales.

So how can you read the final chart after generating it using a Scatter Plot maker?

The Y-axis depicts the dependent metric. On the other hand, the X-axis represents the independent metric under study.

A Scatter plot is a popular choice among seasoned data visualization experts. And this is because most of the data you’ll ever collect has a dependent and an independent variable. Besides, you can easily display tons of insights using limited space. Unlike Pie Charts, you can represent hundreds of data points without clutter.

Also, the Scatter Plot maker can help you to discover shifts, trends, outliers, and other crucial patterns.

In the coming section, we’ll address the following question: when should you use a Scatter Plot maker?

You don’t want to miss this.

When Should You Use a Scatter Plot Maker?

The fundamental goal of the chart is to highlight relationships between two metrics that matter to you.

The dots show the values of individual data points and the overall trend. You can easily forecast the performance as well by extrapolating the resulting curve.

Relationship insights displayed by the visualization chart can be categorized as:

• Linear or nonlinear
• Positive or negative
• Strong or weak

The chart shows the association between two or more data points.

Let’s dive deeper.

If metrics under study increase or decrease together, there’s a positive association. On the other hand, if a metric increases as the other decreases, there’s a negative relationship.

Data points that are positively or negatively related are considered uncorrelated. The Scatter Plot maker’s primary uses are observing and showing associations between two data points.

The dots in a Scatter Plot also report the data’s trend and patterns.

Look at the example below.

The table below has data on various products in the inventory. The goal is to establish the relationship between sales and inventory size (in-stock products).

What’s the go-to chart for the job?

You’re correct if you guessed a Scatter Plot Chart.

Product Types	Products	Sales	No. of Orders	In Stock
Furniture	Beds	90	10	26
Furniture	Cabinets	70	12	16
Furniture	Chairs	190	11	12
Furniture	Clocks	870	16	21
Furniture	Desks	900	25	25
Furniture	Tables	600	23	23
Furniture	Chests	600	42	38
Furniture	Seating	1200	18	43
Stationary	Staplers	590	38	32
Stationary	Sticky Tapes	390	11	35
Stationary	Scissors	590	41	22
Stationary	Desk Tidy	390	18	40
Stationary	Pen Cups	260	15	42
Stationary	Paper Clip	210	2	19
Stationary	Stapler Pins	170	23	44
Stationary	Pencils Box	270	13	25
Grocery	Bakery	140	26	21
Grocery	Bread	110	13	40
Grocery	Seafood	310	12	38
Grocery	Pasta	760	6	35
Grocery	Rice	1500	7	38
Grocery	Cheese	1100	19	39
Grocery	Eggs	150	12	25
Grocery	Oils	280	14	15

Note the difference after visualizing the data above.

Insights

• There’s an inverse relationship between sales and inventory in the stationery category.
• There’s no definite relationship between sales and in stock in the furniture category. The same case applies to

How easy was it to provide a story of the tabular data above using a Scatter Plot maker?

In the coming sections, we’ll tell you the best Scatter Plot maker we used for the task above. Meanwhile, we’ll take you through the importance of using a Scatter Plot generator for data analysis.

Importance of Using a Scatter Plot Generator for Data Analysis?

• Scatter Plot Maker Empowers Accurate Decision-Making

Data in its raw form is difficult to work with, especially if it’s complex and bulky.

While tables are super helpful for organizing your information, they don’t provide a conducive ecosystem for in-depth analysis.

This is where a Scatter Plot maker comes in.

A Scatter Plot Chart is a more convenient medium for interacting with raw data and analyzing the resulting insights.

Here’s an interesting fact.

Our brains process visual content over 60,000 times faster than text and numbers. Besides, we can easily recall visual information longer and more quickly.

Take time and reflect on this

We’re always constantly processing visual data as our eyes are open.

Remember, the speed and effectiveness of visual analysis are significant. And this is because data changes rapidly. So, timely decision-making is the key to getting maximum value from your data.

• Scatter Plots are an Engaging Way of Showcasing Key Insights

Data is not that attractive and appealing in its raw form.

However, it holds an immense value that could help you unlock success in your business. The problem comes in presenting this data to the stakeholders in your business. And this is because some of these individuals may not have the same familiarity with your data.

To alleviate this problem, we recommend you use a Scatter Plot maker.

The visualization design offers an effective and engaging way of presenting insights into your data to others. The chart has a minimalist design to ensure everyone in your team can easily decode insights without struggle.

You can use a very easy-to-use visualization app to make your Scatter Plot Charts. For instance, you can easily add supporting details, such as labels, titles, and other aesthetic details that will make your charts more engaging and appealing.

Keep reading to learn more about this app.

• Displays Tons of Insight using Limited Space

One of the biggest strengths of a Scatter Plot Chart is its ability to depict lots of insights in a limited space.

And this is because each dot takes up very little space. You can easily pack lots of points with the X and Y-axes.

A Scatter Plot Diagram is among a few visualization designs that display a lot of insights in a straightforward format.

• Competition Intelligence Analysis

As a micro or small business owner, you can quickly evaluate the competition for more insights.

Remember, competition plays a significant role in your overall performance. But it can easily detract from your core objective. On the other hand, if you lack insights into what your rivals are doing, it will be challenging to measure their effect on your revenues.

We recommend you try a Scatter Plot to analyze the competitive landscape.

You can leverage a Scatter Plot maker to conduct a competitive analysis, revealing new intelligence. You might discover who you thought was your biggest competitor isn’t so moving needles anymore. Conversely, new players in the market that you weren’t aware of may have taken their place.

In the ensuing section, we’ll take you through the advantages of a Scatter Diagram

Advantages of a Scatter Diagram

• Display Hidden Relationships

A Scatter Chart is arguably one of the visualization designs you can use to show relationships between variables in data.

You just have to check the inclination of the pattern of the dots in the chart. If the pattern is moving from left to right at an inclination, the relationship is negative (inverse).

• Easy to Create and Understand

A Scatter Diagram is amazingly easy to read and interpret.

If metrics under study increase and decrease together, there’s a positive association. On the other hand, if a metric increases as the other decreases, there’s a negative relationship.

Keep reading because, in the coming section, we’ll take you through how to create a Scatter Plot in Excel.

How to Create a Scatter Plot Using Scatter Plot Maker?

Excel is one of the common tools that micro or small business owners like you use to analyze data.

And this is because it has a library of charts, graphs, and maps.

But the spreadsheet application lacks ready-made Scatter Plot Diagrams. In other words, it’s not a reliable Scatter Plot maker.

We’re not advising you to do away with Excel in favor of other expensive tools.

And this is because there’s an amazingly affordable visualization tool that comes as an add-in you can easily install in Excel to access insightful and easy-to-customize Scatter Plot Diagrams. The application is called ChartExpo.

What is ChartExpo?

ChartExpo is an add-in you can easily install in your Excel to access ready-made and visually appealing Scatter Plot Chart.

Features and Benefits

• You have maximum freedom to customize your charts and graphs to your liking.
• ChartExpo is a mere $10 a month after the end of the trial It’s cheaper than Starbucks coffee.
• You don’t need sophisticated design or coding skills to generate stunning, insightful charts for your stories. Save time with this drag-and-drop application.
• Generate any chart in minutes. You don’t need calculations, drawings, or coding to visualize your data.

So, how can you install ChartExpo in Excel to access the ready-made Scatter Plot maker? Keep reading to discover more.

Example

To get started with ChartExpo in Excel, follow the steps below:

• Open your Excel desktop application.
• Open the worksheet and click the Insert button to access the My Apps option.

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

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

• Look for the Scatter Plot, click on its icon to get started, as shown below.

• Fill in your metrics and dimensions by clicking on Create Chart Manually.

• In our case, the key metrics are sales, in stock, and of Orders. On the other hand, our dimensions are products and product types.

• Click the Create Chart button to finalize the process.
• Check out the final chart.

FAQs:

How do you read a Scatter Diagram?

Here’s how you can read and interpret a Scatter Plot.

If metrics under study increase or decrease together, there’s a positive association. On the other hand, if a metric increases as the other decreases, there’s a negative relationship.

Data points that are positively or negatively related are considered uncorrelated.

What is a positive trend in a Scatter Plot?

A trend is regarded as positive if value y increases when x increases. On the other hand, a trend is called negative if the y variable increases but the x decreases.

The dots in the chart show both the values of individual data points and the overall trend.

Wrap Up

Let’s imagine you want to establish whether there’s a correlation between current inflation and global fuel prices.

What’s your go-to chart for the task?

One of the graphs we recommend you use in this scenario is a Scatter Plot Chart.

And this is because it’s best suited for displaying causal relationships between data points.

More so, the visualization design is amazingly easy to read and understand. Remember, we can identify a pattern using dots. For instance, dots progressing an upward-right side symbolize a linear (causal-effect) relationship.

Learning how to use a Scatter Plot maker is a huge leap toward analyzing your data for correlation insights. So, it does not have to be time-consuming or overwhelming, especially if you’re an ardent Excel user.