The accuracy of a rule usually determines uncertainty to the extent. If we have checked the length of the rule against other standard lines, we can assume that this is correct. A rule with marks within a 1mm interval allows you to decide whether the paper edge is closer to either mark. In other words, you can determine whether the paper edge is more or less half between one mark and the next. We could then estimate the accuracy of the measurement at half a millimeter (0.5 mm) under ideal conditions, as the measurements probably suggest that the paper edge is closest to the same mark each time. To make a statement about our uncertainty, we would then need a level of confidence, in which case it would be qualitative: we are very confident that the measures repeated within 0.5 mm will be above or below average. Statements of trust, as some believe, are not a measure of what a “correct” measure is. Instead, a jam instruction describes the probability that a measuring range will ride with the average of a measurement when a study is repeated. This may sound a bit confusing, but consider a study by Yoshikata Morimoto and colleagues who studied the average speed of eight college baseball players (Morimoto et al., 2003). Each of the pitchers had to throw six rope lengths and the average pitch speed was determined at 34.6 m/s (77.4 mph) for a 95% confidence interval of 34.6 ± 0.2 m/s (34.4 m/s at 34.8 m/s).

Later, when he repeated this study, which predicted that each of the eight launchers had to throw 18 lengths of rope, the average speed was determined at 34.7 m/s, exactly within the confidence interval reached in the first study. The accuracy and accuracy of the error is the correspondence between a measured value and the actual value. The error is the difference between a measurement and the actual value of the measurement (the measured amount). Errors do not contain errors. Values resulting from reading the wrong value or error must be explained and excluded from the record. Error is what causes values to differ when one measurement is repeated, and none of the results can be preferred over the others. Although it is not possible to completely eliminate errors to a greater extent, it can be controlled and characterized. Often, more effort is made to determine error or uncertainty to a extent than to achieve the measure itself.

There is uncertainty in all the scientific data, and even the best scientists find a certain degree of error in their measurements.