Experimental error, in a scientific context, refers to the inherent uncertainty and variation that exists in any measurement process. It's not a "mistake" in the conventional sense but rather the difference between a measured value and the true or accepted value of a quantity. All scientific measurements are subject to error, and understanding these errors is essential for interpreting experimental results and drawing valid conclusions.

Two primary categories of experimental error:

• Systematic errors: consistent and repeatable biases in measurements. Systematic errors affect the accuracy of a measurement (how close it is to the true value).
• Random Errors: unpredictable fluctuations in measurements. They can cause the measured values to be sometimes higher and sometimes lower than the true value, with no discernible pattern.