Measurement_DataTreatment - METU Department of Chemical...

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Unformatted text preview: METU Department of Chemical Engineering ChE 320 – Chemical Engineering Laboratory I Experiment 30 - Measurement and Data Treatment 1. OBJECTIVE The aim of the experiment is to evaluate the quality of the measurements statistically. In addition to this, by comparing the results with actual values, determination of the error sources should be defined by doing data evaluation. 2. PRELIMINARY WORK 1. Explain the meanings of arithmetic mean, absolute error, relative error, standard deviation and variance of the sample data briefly and describe how to calculate them. 2. What are the types of errors? Explain. 3. How are detection limit and significant figure related? 4. What is distinguishing of the accuracy and the precision? 5. The following molarities were calculated from replicate standardization of a solution: 0.5026, 0.5029, 0.5023, 0.5031, 0.5025, 0.5032, 0.5027 and 0.5026 M. Assuming no determinate errors, within what range are you 95% certain that the true mean value of the molarity falls? 3. BACKGROUND INFORMATION 3.1. Gaussian Distribution Gaussian distribution is a statistical arrangement of values of a variable showing their observed or theoretical frequency of occurrence. When measuring a physical variable one tries to eliminate systematic errors, so that only accidental errors have to be taken into account. In that case the measured values will spread around the average value, as a Gauss curve. It can be proved that in the case when the average value of a measured value is the 'best value', a Gaussian distribution holds. The 'best value' is here defined as that value, for which the chance on subsequent measurements is maximal. Because in general an estimation of errors is rather rough, the distribution to be used has not to define the error very precise. More important is that the distribution is easy to work has not to define the error very precise....
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Measurement_DataTreatment - METU Department of Chemical...

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