accuracy and precision
Accuracy and precision are two different ways a measurement can be good, and beginners often blur them. Accuracy is how close your result is to the true value. Precision is how close your repeated measurements are to each other, how consistent and tightly clustered, regardless of whether they cluster around the right answer.
The classic picture is a dartboard. Tightly grouped darts far from the bull's-eye are precise but not accurate (a consistent error). Darts scattered all around the bull's-eye average out near the centre, accurate on average but not precise. Darts both tight and centred are accurate and precise; darts scattered and off-centre are neither. In numbers: precision shows up as small random scatter, accuracy as a small gap between your average and the truth.
The distinction matters because the cures differ. Poor precision is beaten by averaging many readings, since random scatter partly cancels. Poor accuracy is not: a miscalibrated scale that always reads 2 g heavy will be wrong no matter how many times you weigh, so you must find and remove the systematic error.
A scale that always reads 2 g too high is precise (same answer every time) but not accurate. Averaging ten weighings will not fix it; only recalibrating will.
Precision is consistency; accuracy is correctness. They are not the same.
You can be precisely wrong. High precision with low accuracy is the dangerous case, because the tight, repeatable numbers look trustworthy.