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Table A.1: Experimental error on the thickness of a glass slab. The resolution lets us place an upper bound on the unobservable but present random fluctuations in the measured quantity.
Learning Goals. Understand how to measure error in a lab experiment. Study how to propagate error from an initial measurement through a calcu- lation. Understand how uncertainty is an integral part of any lab experiment. Introduction. There is no such thing as a perfect measurement.
Measurement error is the amount of inaccuracy. Precision is a measure of how well a result can be determined (without reference to a theoretical or true value). It is the degree of consistency and agreement among independent measurements of the same quantity; also the reliability or reproducibility of the result.
There are three basic categories of experimental issues that students often think of under the heading of experimental error, or uncertainty. These are random errors, systematic errors, and mistakes. In fact, as we will discuss in a minute, mistakes do not count as experimental error, so there are in fact only two basic error categories: random
eliminate error, the goal is know what the errors are, and to get them to be small enough. This lab is designed to give you practice identifying and quantifying sources of error in experiments.
An error is the difference between the measured value and the expected value of something (unavoidable). An uncertainty is a way of expressing or summarizing the error (unavoidable).
precision of your experiment! So, in order to do our quantiative analysis properly and come to a conclusion as to whether it is correct or not, we need to know our errors. 1.1 Random vs. Systemic Error There are two kinds of error that one deals with in the lab: random error and systemic error.
