Titlebook: Measurement Theory for Engineers; Ilya Gertsbakh Textbook 2003 Springer-Verlag Berlin Heidelberg 2003 Measure.Normal.Normal distribution.c

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Comparing Means and Variances,In this section we consider a very important and widely used test in statistics called the .-test which is designed to compare the mean values in two independent normally distributed populations A and B. Let us first consider an example.

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Measurements in Special Circumstances,For sake of simplicity, assume that the measurement results are integers on a unit-step grid, i.e. the measurement results may be ..., –2, –1, –2, –1, 0, 1, 2,... In the notation of Sect. 2.2, the interval between instrument scale readings is . = 1.

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Measurement Uncertainty: Error Propagation Formula,zed results from measuring pull strength. In most real-life situations, the measurement process involves . quantities whose measurement result is subject to uncertainty. To clarify the exposition, let us consider a rather simple example.

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Measuring Population Mean and Standard Deviation,cts. The population in our case is the totality of weight measurements of the daily batch of apples sorted by the device. The experiment consists of weighing a random sample of 20 apples taken from the batch. The results are summarized in Table 2.1.

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Measurement Uncertainty: Error Propagation Formula,zed results from measuring pull strength. In most real-life situations, the measurement process involves . quantities whose measurement result is subject to uncertainty. To clarify the exposition, let us consider a rather simple example.

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Calibration of Measurement Instruments,on in mg/dl in certain substances. For this purpose, a spectrophotometric method is used. Without going into detail, let us note that the response of the measurement device y is the so-called . which depends on the concentration . So, the measurement instrument provides us with a value y, the respon