Calibration of radiocarbon determinations is in principle very simple. If you have a radiocarbon measurement on a sample, you can try to find a tree ring with the same proportion of radiocarbon. Since the calendar age of the tree rings is known, this then tells you the age of your sample.

## Why do radiocarbon dates need to be calibrated How is such calibration achieved?

Calibration of radiocarbon results is needed to account for changes in the atmospheric concentration of carbon-14 over time. These changes were brought about by several factors including, but not limited to, fluctuations in the earths geomagnetic moment, fossil fuel burning, and nuclear testing.

## How will you know if your calibration curve is acceptable?

The r or r2 values that accompany our calibration curve are measurements of how closely our curve matches the data we have generated. The closer the values are to 1.00, the more accurately our curve represents our detector response. Generally, r values ≥0.995 and r2 values ≥ 0.990 are considered good.

## What does a good calibration curve look like?

The r or r2 values that accompany our calibration curve are measurements of how closely our curve matches the data we have generated. The closer the values are to 1.00, the more accurately our curve represents our detector response. Generally, r values ≥0.995 and r2 values ≥ 0.990 are considered good.

## What is a normal calibration curve?

In analytical chemistry, a calibration curve, also known as a standard curve, is a general method for determining the concentration of a substance in an unknown sample by comparing the unknown to a set of standard samples of known concentration.

## Do you include the blank in a calibration curve?

The calibration blank may be included as a data point in the calibration curve if the method includes this as an option. Otherwise, the calibration blank should not be included as a data point in the calibration curve.

## How do you make a calibration curve?

The equation will be of the general form y = mx + b, where m is the slope and b is the y-intercept, such as y = 1.05x + 0.2. Use the equation of the calibration curve to adjust measurements taken on samples with unknown values. Substitute the measured value as x into the equation and solve for y (the “true” value).