How to Find Unknown Value on Excel Graph

Ever look at an Excel chart and wish you could pinpoint a value that isn't one of your original data points? Knowing how to find these in-between or future values - a process known as interpolation and extrapolation - can unlock deeper insights hidden in your data. This guide will walk you through several easy-to-follow methods for finding unknown values directly on your Excel graphs, transforming your static charts into dynamic analytical tools.

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First, The Simple Stuff: Identifying What's Already There

Before diving into unknown values, let's make sure we can easily read the known ones. When you create a chart, Excel lets you see the exact values of your data points with just a click or a hover.

Hover to Reveal

The quickest way to see the value of a specific point on your graph is to simply hover your mouse over it. A small tooltip will pop up displaying the series name, the X-axis value, and the Y-axis value. This is perfect for a quick, one-off check when you're exploring the data visually.

Add Data Labels for Lasting Clarity

If you want all your data point values to be visible at once, data labels are the way to go. This makes your chart much easier to read without constant hovering.

• Click on your chart to select it.
• Click the green “+” icon (Chart Elements) that appears on the top-right corner.
• Check the box next to Data Labels.

Excel will instantly add the Y-values to each data point on your chart. For more control, click the small arrow next to "Data Labels" to choose where the labels appear (Center, Left, Above, Below, etc.) or to include other information like the X-value or series name.

These methods are great for understanding the data you already have. But what about the gaps between these points? That's where trendlines come in.

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Finding Values In-Between with a Trendline Equation

Let's say you're tracking website traffic and you have data for day 1, day 5, day 10, day 15, and so on. What if you want to estimate what the traffic was on day 7? This is "interpolation," and the best way to do it in Excel is by adding a trendline to your chart.

For this to work best, we recommend using a Scatter (XY) chart, as it's designed to show the relationship between two sets of numerical data.

Imagine we have this simple data set of Ad Spend vs. Sales:

We want to find out the estimated sales if we had spent $300.

Step 1: Create a Scatter Chart

First, highlight your data, go to the Insert tab, and select the first Scatter chart option. You’ll get a basic chart showing the relationship between your X (Ad Spend) and Y (Sales) values.

Step 2: Add and Format a Trendline

Now, let's add the trendline to visualize the general direction of our data.

1. Right-click on any of the blue data points on your chart.
2. Select Add Trendline... from the context menu.

A dotted line will appear on your chart, and the "Format Trendline" pane will open on the right side of your screen.

Step 3: Display the Equation on the Chart

This is where the magic happens. The trendline isn't just a visual guide, it's a mathematical formula. By displaying that formula, we can use it to calculate any value along that line.

In the "Format Trendline" pane, scroll down and check two crucial boxes:

• Display Equation on chart
• Display R-squared value on chart

An equation in the format y = mx + b will appear on your chart. This is the formula for your trendline!

• y is the value we want to find (Sales).
• x is the value we already have (Ad Spend).
• m is the slope of the line (how much y changes for every one-unit change in x).
• b is the y-intercept (the value of y when x is 0).

The "R-squared" value tells you how well the line fits your data. A value of 1 means a perfect fit, and values closer to 1 (like 0.98 or 0.99) mean your model is very reliable. Our example shows an R-squared of 0.999, which is excellent.

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Step 4: Use the Equation to Calculate the Unknown Value

From our chart, the equation is y = 12.064x + 60.714.

We want to find the estimated sales (y) for an ad spend of $300 (x). Let's plug x=300 into the equation:

y = (12.064 * 300) + 60.714

You can do this calculation directly in an Excel cell:

=(12.064 * 300) + 60.714

The result is $3,679.91. So, based on our data trend, a $300 ad spend would likely generate around $3,680 in sales.

Forecasting Future Values with Extrapolation

Interpolation is about finding values within your data range. "Extrapolation" is about forecasting values beyond your existing data range. We can use the same trendline tools to make these predictions.

Method 1: Extending the Trendline Visually

If you want a quick visual forecast, you can extend the trendline on the chart.

1. Right-click the trendline and choose Format Trendline...
2. In the pane on the right, look for the Forecast section.
3. Enter a value in the Forward box. This represents the number of X-units you want to project into the future.

For example, our Ad Spend data goes up to $700. If we enter 200 in the Forward box, the line will extend out to an x-value of $900 on the graph, giving you a visual representation of your future trend.

Method 2: Using the Trendline Equation for a Precise Forecast

For a precise number, you use the exact same equation as before. Let's say we want to predict our sales if we increase our Ad Spend to $850.

Our equation is still y = 12.064x + 60.714. We just plug in a new x-value:

y = (12.064 * 850) + 60.714

The result is $10,315.11. Our forecast suggests that an ad spend of $850 would result in over $10,300 in sales.

A Quick Word of Caution: Extrapolation is a prediction, not a guarantee. The further your forecast extends beyond your actual data, the less reliable it becomes, as unforeseeable factors could change the trend.

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A Faster Method: Using Excel's FORECAST.LINEAR Function

Displaying the equation on the chart is fantastic for visual presentations and understanding the model. But if you need to calculate lots of unknown values quickly, there’s an even faster way: the FORECAST.LINEAR function.

This function does the exact same linear regression calculation as the trendline but puts the answer directly into a cell, skipping the visual steps.

The syntax for the function is:

=FORECAST.LINEAR(x, known_y's, known_x's)

• x: The new x-value you want to find the y-value for.
• known_y's: Your range of existing y-values (sales).
• known_x's: Your range of existing x-values (ad spend).

Let's use our same dataset to find the projected sales for a $300 ad spend. Assume our Ad Spend values are in cells A2:A6 and our Sales values are in B2:B6.

In any empty cell, type the following formula:

=FORECAST.LINEAR(300, B2:B6, A2:A6)

Excel instantly returns $3,679.92 — the exact same value we calculated manually, but in a fraction of the time. This function is incredibly powerful when you need to run multiple "what-if" scenarios without cluttering up your chart with formulas.

Final Thoughts

Finding unknown values in an Excel graph takes your data analysis from simply reporting what happened to predicting what might happen next. Whether you use the visual trendline equation for presentations or the speedy FORECAST.LINEAR function for quick calculations, you now have the tools to uncover insights that exist between and beyond your data points.

While Excel is fantastic for detailed manual analysis, sometimes you need answers without hunting down formulas or fine-tuning chart settings. Instead of building these charts and calculations yourself, we designed Graphed to do the work for you. You can connect your marketing and sales data, then just ask in plain English something like, "project our sales for a $850 ad spend" and get a real-time visualization instantly. It streamlines your workflow by delivering actionable insights in seconds, allowing you to focus on strategy, not spreadsheets.