It is important to consider the experimental error in all empirical results because it is a measure of the accuracy of the results and the reliability of the method. It gives insight on how wrong the results are and how the method can be improved.
Accuracy
No measurement is completely accurate. There is always some degree of error in the measurements. The closeness of a measurement to the true value is called accuracy.
Precision
Precision is how close measurements are to each other. Higher precision instruments allow the measurements to be very close to each other and give a better approximation of a measurement and increases the accuracy of the reading as well.
Experimental errors are considered to ensure that the data or the method is accurate and reliable. The lower the experimental error, the more confidence we have that the measurement is near the true value. It also provides insight about how to optimize the method to yield better results.
Kinds of Experimental Error
Random error
Random errors are errors that are beyond the control of the experimenter. These are variations that happen by chance and may be reduced by performing multiple trials and averaging the results.
Systematic error
Errors incurred by the way the experiment was conducted are called systematic errors. Their effect cannot be reduced by doing more trials but by changing the design or the method used to obtain the results.
Keywords: accuracy, precision, experimental error
