A Level Physics Error Analysis
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Slideshare uses cookies to improve functionality and performance, and to provide you with relevant advertising. If you continue browsing the site, you agree to the use of cookies on this website. See our Privacy Policy and physics error analysis formula User Agreement for details. SlideShare Explore Search You Upload Login Signup Home Technology Education error analysis physics lab report More Topics For Uploaders Get Started Tips & Tricks Tools Physics 1.2b Errors and Uncertainties Upcoming SlideShare Loading in …5 × 1 error analysis in physics experiments 1 of 16 Like this presentation? Why not share! Share Email Topic 2 error & uncertainty- part 3 byNoel Gallagher 10428views Uncertainty and equipment error byChris Paine 52892views IB Chemistry on uncertainty error c... byLawrence
Error Analysis Physics Example
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Physics Error Propagation
1 Physics and physical measurementThe realm of physicsMeasurement & uncertaintiesVectors & scalars2 MechanicsKinematicsForces & dynamicsWork, energy & powerUniform circular motion4 Oscillations and wavesKinematics of simple harmonic http://www.slideshare.net/thephysicsteacher/12b-errors-and-uncertainties motion (SHM)Energy changes during simple harmonic motion (SHM)Forced oscillations & resonanceWave characteristicsWave properties Measurement and uncertainties1.2.1 State the fundamental units in the SI system.Many different types of measurements are made in physics. In order to provide a clear and concise set of data, a specific system of units is used across all sciences. http://ibguides.com/physics/notes/measurement-and-uncertainties This system is called the International System of Units (SI from the French "Système International d'unités"). The SI system is composed of seven fundamental units: Figure 1.2.1 - The fundamental SI units Quantity Unit name Unit symbol mass kilogram kg time second s length meter m temperature kelvin K Electric current ampere A Amount of substance mole mol Luminous intensity candela cd Note that the last unit, candela, is not used in the IB diploma program.1.2.2 Distinguish between fundamental and derived units and give examples of derived units.In order to express certain quantities we combine the SI base units to form new ones. For example, if we wanted to express a quantity of speed which is distance/time we write m/s (or, more correctly m s-1). For some quantities, we combine the same unit twice or more, for example, to measure area which is length x width we write m2. Certain combinations or SI units can be
absolute error. Absolute error is the actual value of the error in physical units. For example, let's say you managed to measure the length of your dog L to be 85 cm with a precision 3 cm. You https://phys.columbia.edu/~tutorial/reporting/tut_e_3_2.html already know the convention for reporting your result with an absolute error Suppose you also regularly monitor the mass of your dog. Your last reading for the dog's mass M, with absolute error included, is Which measurement is more precise? Or in other words, which one has a smaller error? Clearly, we cannot directly compare errors with different units, like 3 cm and 1 kg, just as we cannot directly compare apples and oranges. However, there should be a error analysis way to compare the precision of different measurements. Enter the relative or percentage error. Let's start with the definition of relative error Let's try it on our dog example. For the length we should divide 3 cm by 85 cm. We get 0.04 after rounding to one significant digit. For the mass we should divide 1 kg by 20 kg and get 0.05. Note that in both cases the physical units cancel in the ratio. Thus, relative error is just a error analysis in number; it does not have physical units associated with it. Moreover, it's not just some number; if you multiply it by 100, it tells you your error as a percent. Our measurement of the dog's length has a 4% error; whereas our measurement of the dog's mass has a 5% error. Well, now we can make a direct comparison. We conclude that the length measurement is more precise. Finally, let us see what the convention is for reporting relative error. For our dog example, we can write down the results as follows The first way of writing is the familiar result with absolute error, and the second and third ways are equally acceptable ways of writing the result with relative error. (Writing the result in the parentheses form might seem a little bit awkward, but it will turn out to be useful later.) Note that no matter how you write your result, the information in both cases is the same. Moreover, you should be able to convert one way of writing into another. You know already how to convert absolute error to relative error. To convert relative error to absolute error, simply multiply the relative error by the measured value. For example, we recover 1 kg by multiplying 0.05 by 20 kg. Thus, relative error is useful for comparing the precision of different measurements. It also makes error propagation calculations much simpler, as you will see in the next cha