Are five weighings 2.486–2.488 g precise and accurate?

The measurements are precise with a tight spread, and the average of two point four eight six grams is the best estimate of the mass assuming there is no systematic error.

Think of precision like hitting the same spot on a target many times, even if that spot is not the bullseye, and here all five weighings are very close: two point four eight six, two point four eight seven, two point four eight five, two point four eight four, and two point four eight eight grams. To get the best single value from those numbers you add them and divide by how many measurements you took, which gives two point four eight six grams as the average or mean. That average is a good estimate because the individual values cluster tightly around it, but it only represents random repeatability, not whether the scale gives a correct value overall. If the scale has a bias or a zero offset, every measurement could be precise but wrong in the same way.

A common mistake is thinking precision means accuracy, so do not assume your average is the true mass without checking calibration, and the practical tip is to verify the balance with a known standard weight. Another error is ignoring outliers; if one number were far from the others you would investigate whether it was a recording or instrument error, and the fix is to repeat that weighing rather than discard data casually. A third misconception is reporting too many digits from a balance when uncertainty is larger, so round your reported result to reflect the scale of variation seen in your measurements.

You can find more videos and resources on experimental error, precision, and accuracy at w w w dot gumball degree dot com.

Precision vs Accuracy: Five Weighings at 2.486 g

1. Precision means repeated close measurements
2. Calculate mean by summing and dividing
3. Mean equals best estimate here
4. Tight cluster shows repeatability
5. Check for systematic bias separately

Mistakes on Precision, Outliers, Significant Digits

1. Confusing precision with accuracy
2. Ignoring outliers instead of checking
3. Reporting too many significant digits

precision, accuracy, weighings, massmeasurement, significantfigures, outliers, experimentalerror, mean, calibration, labtechnique