Measurement Error (also called Observational Error) is the difference between a measured quantity and its true value. It includes random error (naturally occurring errors that are to be expected with any experiment) and systematic error (caused by a mis-calibrated instrument that affects all measurements). For example, let’s say you were measuring the weights of 100 marathon athletes. The scale you use is one pound off: this is a systematic error that will result in all athletes body weight calculations to be off by a pound. On the other hand, let’s say your scale was accurate. Some athletes might be more dehydrated than others. Some might have wetter (and therefore heavier) clothing or a 2 oz. candy bar in a pocket. These are random errors and are to be expected. In fact, all collected samples will have random errors — they are, for the most part, unavoidable. The significant figures (also known as the significant digits or precision) of a number are digits that carry meaningful contributions to its measurement resolution. This includes all digits except All leading zeros. For example, "013." has two significant figures: 1 and 3; Trailing zeros when they are merely placeholders to indicate the scale of the number (exact rules are explained at identifying significant figures); and Spurious digits introduced, for example, by calculations carried out to greater precision than that of the original data, or measurements reported to a greater precision than the equipment supports.

errors in measurement +3 more

by Akansha pandey

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Solving the sample papers makes students more prepared for the examinations as they solve various types of problems and answer various questions. It will also give the students an idea about the area where they are strong, and those areas where they need improvisation.

physics sample paper

by Shiksha Choudhary

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