Observational error, also known as measurement error, is the difference between the measured value and the true value of a quantity. It is often caused by limitations in the measuring equipment or techniques, as well as human error.
Observational error is different from random error in that it is a systematic error that consistently affects the measurement in the same way. Random error, on the other hand, is unpredictable and can occur in any direction, resulting in a spread of measurements around the true value.
While it is not possible to completely eliminate observational error, it can be reduced through careful calibration of equipment, use of precise measurement techniques, and multiple measurements to account for any inconsistencies.
Observational error can impact scientific research by introducing uncertainties and inaccuracies into the data, leading to incorrect conclusions and potentially hindering the progress of research. It is important for scientists to account for and minimize observational error in their experiments and studies.
No, identical measurement results are not always accurate. While it is a good sign of precision, it does not guarantee accuracy. If the measurements are affected by observational error, they may be consistently inaccurate and result in identical measurements that are not reflective of the true value.