Error Analysis Significant Figures and Error Propagation.

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Presentation transcript:

Error Analysis Significant Figures and Error Propagation

Precision vs Accuracy Precision: how small the random error is. Accuracy: how close the measured quantity is to the actual value. High accuracy means small systematic error.

Random Error & Systematic Error Random Error: Error due to uncontrollable fluctuations Examples: human reaction time, fluctuations in surrounding temperature, pressure influencing measuring apparatus Systematic Error: Unknown defects or inadequate calibration of instruments. Can in principle be eliminated completely Examples: A ruler that has one end cut off so all measurements of length is off by the same amount.

Instrument Uncertainty Every instrument has its limit, or resolution, beyond which one cannot reliably measure a quantity. We will talk about how to find the instrument uncertainty for digital and graduated instrument. In most cases, however, the instrument is merely the lower bound on the uncertainty. Most measurements are dominated by random error (find by statistical analysis on multiple measurement, see below) so instrument uncertainty is not often used in the error calculation. Rule of thumb: Only use instrument uncertainty if only one measurement is possible, or if the random error turns out to be smaller than the instrument uncertainty (highly unlikely).

Instrument Uncertainty (Digital Instrument) For a digital instrument, the last digit is the uncertainty. For example 2.34g means (2.34±0.01)g.

Instrument Uncertainty (Graduated Instrument ) Optimistic: Try to guess to one digit beyond the smallest scale A typical ruler is graduated to 1mm, read length to 0.1mm (thus the error is ±0.1mm) Conservative Set uncertainty to half of the smallest scale A typical ruler is graduated to 1mm, read length to 0.5mm (thus the error is ±0.5mm)

Instrument Uncertainty (Judgment call) Sometimes you may want to increase the uncertainty beyond even the conservative instrument uncertainty if the measurement was not carried out in ideal situations. For example, in measuring the diameter of a tennis ball with a ruler, it is difficult to say if your ruler is really lined up with the diameter, so it does not make sense to use 0.5mm as the uncertainty. If you can make only one measurement, the uncertainty to use is a judgment call. In general, however, one should use multiple measurements and use the statistical analysis below (using standard deviation) to find the uncertainty.

Examples Absorbance: 0.236±0.001 (optimistic choice) Absorbance: 0.240±0.005 (conservative choice) Transmittance: 58.0±0.5 (conservative: scale for transmittance too small to see clearly)

Mean (average) Repeated measurements: Common mistake: Too many digits Usually, the mean has only slightly better precision, so keep to at most one higher significant figure. The mean above should be either 3.3 or 3. We will learn how to find the uncertainty below.

(Sample) Standard Deviation σ The smaller the standard deviation, the more better are your data.

Relation to Random Uncertainty

Example Find the σ of the following measurement of length x : 11.3cm, 11.7cm, 12.0cm, 11.8cm

Standard deviation 68% of probability lying within a width of 2σ.

Using Excel x CountMean of xError of xError of mean of x "=COUNT(…)""=AVERAGE(…)""=STDEV.S(…)""=error/SQRT(count)"

Arithmetic Addition and Subtraction

Scientific Notation Express numbers to the same exponents during addition and subtraction.

Arithmetic Multiplication and Division No need to express numbers to the same exponents during multiplication and division.

Propagation of Error Addition and Subtraction

Example

Propagation of Error Multiplication and Division

Example (Cont.)

Mixed Operation

Changing significant figure

Summary

Exercise Significant Figures

Propagation of Error

Credits Most of the materials in this lecture is taken directly from: [Unfortunately the link is no longer working.] Download and read the chapter directly for more details.