The Reliability of a Measurement

Recall from Section 1.1 that carbon monoxide is a colorless gas emitted by motor vehicles and found in polluted air. The table below shows carbon monoxide concentrations in Los Angeles County as reported by the U.S. Environmental Protection Agency (EPA) over the period 1990-2010  

The first thing you should notice about these values is that they decrease over time. For this decrease, we can thank the Clean Air Act and its amendments, which have resulted in more efficient engines and specially blended fuels and consequently in cleaner air in all major U.S. cities over the last 30 years. The second thing you might notice is the number of digits to which the measurements are reported. The number of digits in a 

Scientific measurements are reported so that every digit is certain except the last, which is estimated. 

The first three digits are certain the last digit is estimated. 

The graduated cylinder shown at the right has markings every 0.1 mL. Report the volume (which is read at the bottom of the meniscus) to the correct number of digits. (Note The meniscus is the crescent-shaped surface at the top of a column of liqnid.) 

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A term used in statistics to indicate the reliability of a measured result. A confidence level of 90% indicates that there is a 10% chance that the result is not reliable. 

The word accuracy is used to indicate the reliability of a measurement or an observation, but it is, more specifically, a measure of the closeness of agreement between an experimental result and the true value. Thus, the accuracy of a test method is the degree of agreement of individual test results with an accepted reference value. 

The term reliable data is closely related to data quality. It is the quality of a measurement, and its control and assurance make it possible to determine and prove the reliability of a measurement. 

Most experimental measurements in the laboratory are inexact ntmbers that have particular uncertainties attached to them. The numbers represent approximations rather than exact quantities. The concept of significant figures is designed to indicate the reliability of a measurement or the uncertainty in that measurement and to provide the maximum amount of information and no misinformation. 

The more useful and modem metrological approach to express the reliability of a measurement result is a statement of measurement uncertainty that is associated with every measurement result. It is not the goal of this method to approach the tme value as close as possible. Rather, the objective is to assign an interval of reasonable values to the measurand. Instead of searching for systematic and random errors, components of measurement uncertainty are assigned and grouped into two categories. Type A and Type B, where Type A components... 

Another of the various parameters commonly used by chemists to measure the reliability of a measurement is called the average error... 

When we report the result of a measurement a , there are two things a person reading the report wants to know the magnitude (size) of the measurement and the reliability of the measurement (its scatter ). If measuring errors are random, as they very frequently are, the magnitude is best expressed as the arithmetic mean p of N repeated tr ials xi... 

The reliability of a product is the measure of its ability to perform its intended function without failure for a specified time in a particular environment. Reliability engineering has developed into two principal areas part and system. Part reliability is concerned with the failure characteristics of the individual part to make inferences about the part population. This area is the focus of Chapter 4 of the book and dominates reliability analysis. System reliability is concerned with the failure characteristics of a group of typically different parts assembled as a system (Sadlon, 1993). 

The reliability of a mean is judged by the distribution of the individual measurements about the mean. There are two generally used measures of the spread (the scatter) of a set of observations, namely the range R and the standard deviation s. ... 

For the characterization of the reliability of analytical measurements the terms precision, accuracy, and trueness have a definite meaning. 

It is important to have some knowledge of the reliability of all measurement results. Measurement uncertainty is the parameter used to describe the range within which the true value (or right answer) for a particular measurement is expected to lie. Evaluating measurement uncertainty involves a number of distinct steps, which are described in this chapter. 

Once the reliability of a replicate set of measurements has been established the mean of the set may be computed as a measure of the true mean. Unless an infinite number of measurements is made this true mean will always remain unknown. However, the t-factor may be used to calculate a confidence interval about the experimental mean, within which there is a known (90%) confidence of finding the true mean. The limits of this confidence interval are given by ... 

The evaluation of robustness should be considered in the development of the assay and will depend on the type of procedure under development. It must show the reliability of a method with respect to deliberate variations in method parameters. If measurements are susceptible to variations in analytical conditions, the analytical conditions should be suitably controlled or a precautionary statement might be included in the procedure. One consequence of the evaluation of robustness may be that a series of system suitability parameters is established to ensure that the validity of the analytical procedure is maintained whenever used. Typical parameters to be tested would be the following sample concentration, sample stability, labeling variability (if applicable), injection variability, reagent lot-to-lot variability, and capillary vendor. 

Measure the concentration of analyte in several identical aliquots (portions). The purpose of replicate measurements (repeated measurements) is to assess the variability (uncertainty) in the analysis and to guard against a gross error in the analysis of a single aliquot. The uncertainty of a measurement is as important as the measurement itself, because it tells us how reliable the measurement is. If necessary, use different analytical methods on similar samples to make sure that all methods give the same result and that the choice of analytical method is not biasing the result. You may also wish to construct and analyze several different bulk samples to see what variations arise from your sampling procedure. 

Integration by these devices is clearly more accurate and precise than by manual measurements and precision of results is in the order of 0.5%. Peak identification algorithms approach the reliability of a trained operator. Concentrations are normally calculated by one of four standard calculation procedures. 

Measurements of absolute total cross sections for Pgl are complicated by two facts (1) it is not easy to reliably determine the metastable current used in a beam experiment and (2) the cross sections usually vary considerably in the thermal-energy range, so that an exact knowledge of the energy distribution of the metastables used is necessary for estimation of the result of a measurement. 

Any measurement is only as good as the skill of the person doing the work and the reliability of the equipment being used. You ve probably noticed, for instance, that you get slightly different readings when you weigh yourself on a bathroom scale and on a scale at the doctor s office, so there s always some uncertainty about your real weight. The same is true in chemistry—there is always some uncertainty in the value of a measurement. 

Reliability Large numbers of redundant sensors allow signal averaging to improve accuracy and the use of fault detection algorithms to detect the failure of individual array elements.36 For example, the variance of a measurement based on the average of N identical sensors is... 

The numerical value of every observed measurement is an approximation, since no physical measurement—of temperature, mass, volume, etc.—is ever exact. The accuracy of a measurement is always limited by the reliability of the measuring instrument. 

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