How to Find R Value in Google Sheets Graph

Trying to figure out if your marketing spend actually drives sales, or if more social media posts lead to more website traffic, can feel like guesswork. You have the data in front of you, but connecting the dots isn't always straightforward. Luckily, Google Sheets has a powerful, yet simple, feature that cuts through the noise: the R-squared value, which tells you how well one set of data can predict another. This article will walk you through exactly how to find and understand the R-squared value on a Google Sheets graph, so you can stop guessing and start making data-backed decisions.

What is R-Squared? (And Why It Matters for Your Business)

Before diving into the "how," let's quickly cover the "what" and "why." In statistical terms, R-squared is called the "coefficient of determination." While that sounds intimidating, the concept is surprisingly simple. R-squared measures the strength of the relationship between two variables.

Imagine you're tracking two things:

• Your monthly budget for Facebook Ads (Variable X, the independent variable).
• Your monthly revenue from your Shopify store (Variable Y, the dependent variable).

You want to know: "How much of the change in my revenue can be explained by the change in my ad spend?" R-squared gives you the answer as a percentage.

The value of R-squared ranges from 0 to 1:

• An R-squared of 1 means there is a perfect correlation. In our example, it would mean that 100% of the changes in your revenue are explained by your ad spend. Every single dollar increase in ad spend corresponds to a predictable increase in revenue. (This is extremely rare in the real world).
• An R-squared of 0 means there is absolutely no correlation. Your ad spend has zero relationship with your revenue fluctuations.
• A value somewhere in between, like 0.75, would mean that 75% of the variation in your revenue can be explained by your ad spend. The other 25% is due to other factors (like seasonality, email campaigns, organic traffic, a great blog post, etc.).

For most marketing and sales analyses, an R-squared value above 0.7 is generally considered a strong correlation, 0.5-0.7 is moderate, and below 0.4 is weak. By understanding this single number, you can get a powerful, at-a-glance idea of whether your strategies are having a predictable impact on your results.

It helps you answer crucial business questions:

• Does spending more on ads reliably lead to more revenue?
• Is there a strong connection between the number of sales demos our team completes and the number of deals we close?
• Do more blog posts correlate with higher organic search traffic?

Now, let's get that value on a chart.

Finding R-Squared on a Graph: The Step-by-Step Guide

Visualizing your data is the most intuitive way to see the relationship between two variables. Adding a trendline and the R-squared value gives you the statistical proof to back up what you see. Let's use the example of tracking monthly Ad Spend vs. Website Revenue.

Step 1: Get Your Data Ready

First, you need your data organized in two columns in Google Sheets. Your "cause" variable (independent variable) should be in the first column, and your "effect" variable (dependent variable) should be in the second. For our example, Ad Spend is the independent variable, and Website Revenue is the dependent one.

Your sheet should look something like this:

Step 2: Create a Scatter Plot

A scatter plot is the perfect chart type for this job because it puts a single point on the graph for each pair of values, allowing you to see the pattern clearly.

1. Click and drag to highlight your two data columns (e.g., "Ad Spend" and "Website Revenue," including the headers).
2. Go to the top menu and click Insert > Chart.
3. Google Sheets will often default to a Line Chart or Bar Chart. In the Chart editor on the right, under the "Setup" tab, open the "Chart type" dropdown menu and select Scatter chart.

Now you should see a chart with dots representing each month's ad spend and revenue.

Step 3: Add a Trendline to Your Chart

The trendline is a straight line that shows the general direction of your data. If the dots on your scatter plot are roughly trending up and to the right, your trendline will reflect that positive relationship.

1. In the Chart editor, click on the Customize tab.
2. Click on the Series dropdown to open its options.
3. Scroll down a bit, and you'll see a checkbox for Trendline. Check it.

A line will immediately appear on your chart, cutting through your data points.

Step 4: Show the R-Squared Value

This is the final and most important step. With the trendline now on your chart, you can easily add the R-squared label.

1. Right below the Trendline option in the "Series" section, you’ll see some new options appear. Find the dropdown menu for Label.
2. Click on the dropdown and select Use Equation. This will show the linear equation for your trendline.
3. Just below that, check the box that says Show R².

You'll now see the R-squared value appear on your chart, usually near the trendline equation. Success! You have visually confirmed the strength of the relationship between your two variables.

Making Sense of Your R-Squared Value

Finding the R-squared value is easy - the real power comes from understanding what it tells you. Let’s say your chart shows R² = 0.92. What does that mean for your business?

It means that 92% of the variation in your monthly revenue can be explained by the variation in your ad spend. That is a very strong positive relationship. This insight gives you confidence that increasing your ad budget is highly likely to increase your revenue.

What if the value was much lower, like R² = 0.21? This suggests a weak relationship. Only 21% of your revenue changes can be tied to ad spend. Pouring more money into ads may not be your best bet for growth. This is an actionable insight! It signals that you should investigate other factors. Maybe your email list generated most of the sales one month, or a partnership drove a ton of referral traffic. These are the things you need to look into.

A Quick Warning: Correlation is Not Causation

This is a critical point. A high R-squared shows a strong correlation, but it doesn't automatically prove that one thing causes the other. A classic example is that ice cream sales and shark attacks are highly correlated. Does eating ice cream cause shark attacks? No. A third variable, a hot summer, causes an increase in both.

In business, you might notice your social media follower count and your revenue are both rising with a high R-squared value. But maybe both are being driven by a powerful PR campaign or a successful new product launch. Always use your business context to interpret the data. R-squared is a starting point for analysis, not the final answer.

Advanced Tip: Calculate R-Squared With the RSQ Formula

What if you just want the number and don't need the chart? Google Sheets has a dedicated formula for that: RSQ.

This is incredibly useful for dashboards or summary tables where you just need the value itself without the visual clutter of a graph.

How to Use the RSQ Function

The syntax is simple:

=RSQ(data_y, data_x)

• data_y: This is your range of dependent data (the "effect"). In our example, it would be the "Website Revenue" column.
• data_x: This is your range of independent data (the "cause"). In our example, it would be the "Ad Spend" column.

Using our sample table from earlier, assuming "Website Revenue" is in cells C2:C7 and "Ad Spend" is in cells B2:B7, you would type this formula into an empty cell:

=RSQ(C2:C7, B2:B7)

Press Enter, and Google Sheets will instantly return the R-squared value. It’s the exact same number you'd find on the chart, but you got it in seconds without ever having to make a visual representation.

When to Use the Graph vs. the Formula

• Use the graph technique when you're preparing a presentation or report. The visual impact of seeing the data points and the trendline together is powerful for explaining the relationship to colleagues or clients.
• Use the RSQ formula when you need to quickly check a correlation or when you're building a dashboard where you want to show the metric without the full chart taking up space.

Final Thoughts

Finding the R-squared value on a Google Sheets graph is a straightforward way to go beyond surface-level data and measure the strength of the relationship between different parts of your business. By adding a trendline and checking a single box, you unlock a powerful insight that can help you validate your strategies and make better decisions moving forward.

Of course, manually building these kinds of reports in spreadsheets across all your different data sources - from Google Analytics and Facebook Ads to Shopify and Salesforce - can quickly become a full-time job. We created Graphed to solve this problem for good. Instead of exporting CSVs and fighting with chart editors, you can connect your data sources in a few clicks and just ask for the analysis you need in simple, plain English - Graphed automatically builds the real-time dashboards and reports for you, so you can spend less time digging and more time acting.