Excel has built-in features that you can use to display your calibration data and calculate a line that suits you best. This can be helpful when writing a chemistry lab report or programming a correction factor into an equipment.

In this article, we'll look at how to use Excel to create a chart, a linear calibration curve, display the calibration curve, and then set up simple formulas using the SLOPE and INTERCEPT function to use the calibration equation in Excel.

## What is a calibration curve and how is Excel useful when creating one?

To perform a calibration, compare the reading of a device (such as the temperature as a thermometer shows) to known values called standards (such as freezing and boiling point in water). This allows you to create a series of data pairs that you then use to develop a calibration curve.

A two-point calibration of a thermometer with freezing and boiling point in water would have two data pairs: one from when thermometer is placed in ice water (32 ** ° ** F or 0 ** ° ** C) and one in boiling water (21

**°**F or 100

**°**] C). When plotting the two data pairs as dots and drawing a line between them (the calibration curve), you assume that the thermometer's response is linear, you can choose any point on the line corresponding to the value the thermometer shows and you can find the corresponding "true" temperature.

Then the line essentially fills the information between the two known points so that you can reasonably be sure when estimating the actual temperature when the thermometer reads 57.2 degrees, but

Excel has functions that make it possible to plot the data heat graphically. in a chart, add a trend line (calibration curve) and show the calibration curve equation on chart. This is useful for a visual display, but you can also calculate the formula for the line using Excel's SLOPE and INTERCEPT functions. When you enter these values into simple formulas, you can automatically calculate the "true" value based on any measurement.

## Let's look at an example

In this example, we will develop a calibration curve from a series of ten data pairs, each consisting of an X value and a Y value. The X values will be our "standards" and they can represent everything from the concentration of a chemical solution that we measure using a scientific instrument to the input variables in a program that controls a marble launch machine. Y values will be the "responses" and they would represent the reading of the instrument provided when measuring each chemical solution or the measured distance from how far away from the starter marble landed at each input value.

After we graphically displayed the calibration curve, we use the SLOPE and INTERCEPT functions to calculate the calibration line formula and determine the concentration of an "unknown" chemical solution based on the instrument reading or determine which input we should give the program so that the marble lands a certain distance from launch.

### Step One: Create Your Chart

Our simple copy worksheet consists of two columns: X value and Y value. [19659003]

Let's start by selecting data to plot in the chart.

First select the column cells "X-Value". [19659003]

Now press the Ctrl key and then click Y-Value column cells.

[19659003] Go to the "Insert" tab.

tab

Navigate to the "Chart" menu and select the first option from the "Scatter" drop-down menu.

] Select the series by clicking on one of the blue dots.

Right-click on one of the points and then select the "Add trend line" option.

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On the right side of the screen the "Format Trendline" menu appears. Select the boxes next to "Show equation on chart" and "Show R-squared value on chart." R-squared value is a statistic that tells how close the line fits the data. The best R-squared value is 1,000, which means that each data point touches the line. As the differences between the data points and the line grow, the r-squaring value drops, with 0,000 being the lowest possible value.

The equation and R-squared statistics of the trend line will be displayed on the chart. Note that the correlation of data is very good in our example, with an R-squared value of 0.988.

The equation is in the form "Y = Mx + B" where M is the slope and B is y

Now that the calibration is complete, let's work on customize the chart by editing the title and adding axis titles. [19659003] To change the table title, click on it to select the text.

Now type a new title describing the chart.

To add titles to the x-axis and the y-axis, navigate first to Chart Tools> Design.

Now navigate to Axis Titles> Prim

To rename the axis title, first, select the text and then enter a new title.

Now, header to axis titles> Primary vertical.

An axis title is displayed.

Rename this title by selecting the text and entering a new title.

Your chart is now ready.

### Step two: Calculate the line equation and the R-squared statistics

Now let's calculate the line equation and R-squared statistics using Excel's built-in SLOPE, INTERCEPT, and CORREL features.

To our sheet (in line 14) we have added titles for the three functions. We perform the actual calculations in the cells under these titles.

First, we should calculate SLOPE. Select cell A15.

Navigate to Formulas> More Functions> Statistical> SLOPE.