P-error

This determines the switching pattern of the inverter unit, based on the T and

error signals, obtained from the torque and flux comparators. Since these signals arc obtained at very high speed, the inverter IGBTs are also switched with an equally high speed to provide a quick response and an accurate T and N. 

Table 21.3 Relationship between Type 1 (a) and Type 2 (P) errors and accepting the null hypothesis (HO) and rejecting the alternative hypothesis (HI)...

From a composite report of the QUANT-3 analysis of the 1.0% vinyl silanized aluminum hydroxide sample using the other concentrations as standards, the calculated concentration (1.0%) is within experimental error, while the peak-to-peak (p/p) error of 0.00028 refers to the remaining residuals of the unknown... 

Figure 5.9 Uninhibited incipient hydrate T and P errors (absolute) for all hydrates (1685 pts).

FIGURE 5.11 Hydrate formation P error (absolute) for all inhibited hydrates. 

In Figure 18 experimental and IGLO/6-31G(d) chemical shifts of 45 are com-pared Experimental chemical shifts do not agree with chemical shifts calculated for the two HF/6-31G(d) minima structures or any structure close to 45a or 45c. Mean deviations A between calculated and experimental shifts are as large as 40 ppm, thus exceeding normal IGLO/6-31G(d,p) errors by a factor of 6 and more. Clearly, IGLO... 

The power or desired probability of detecting the required mean treatment difference, i.e. the level of chance for accepting a Type II (P) error. For most controlled trials, a power of 80-90% (0.8-0.9) is frequently chosen as adequate, though higher power is chosen for some studies. 

Finlay WH, Stapleton KW, Zuberbuhler P. Errors in regional lung deposition predictions of nebulized salbutamol sulphate due to neglect or partial inclusion of hygroscopic effects. Int J Pharm 1997 149 63-72. 

Do NOT Reject Null Hypothesis. .Risk of Type II, p error... 

Ducharme, M. B., Prim, J., and Tikuisis, P. "Errors in Heat Flux Measurements Due to the Thermal Resistance of Heat Flux Disks." Journal of Applied Physiology 69, no. 2 (1990) 776-84. 

In the EU, and also in other countries that have adopted regulations or guidelines based on the EU approach, the interpretation of analytical results and regulatory decisions is made on the basis of those results that depend on the method performance characteristics known as the detection capability and the decision limit. The detection capability (CCfi) is defined in point 1.12 of the Annex to Commission Decision 2002/657/EC. CCP as the smallest content of the analyte that may be detected, identified, and/or quantified in a sample with an error probability of p. The P error is the probability that the tested sample is truly non-compliant even though a compliant measurement has been obtained. For screening tests the P error (the false-compliant rate) should be <5%. 

An appropriate sample size, or number of replicates, can be calculated for the type of statistical test by using the a and P error, the minimal detectable difference between two test procedures, and the variability (standard deviation) of data determined from previous neutralization system validations. The statistical test chosen to detect if there was a significant comparative increase or decrease in microorganism populations is the two-tailed, pooled Student s f-test. Both and values have been determined, 0.05 and 0.10, respectively. The minimal detectable difference is the minimal difference between samples from two procedures that the researcher would consider as significant and would want to be assured of detecting. Minimal differences that have been published are 0.15, 0.20, and 0.30 log 10 differences between data from Phase 1 and those from other phases [4,19,20]. The 0.15 logic difference will be used for this validation, because it is the most conservative and is from a validation test that involves multiple samples (replication) and a statistical analysis [4]. The final requirement, variability of the data, will be difficult to establish, especially because many researchers will be performing this validation for the first time. If past data are unavailable, then an option is to use an excessive sample size (at least 10) and use the data from that validation to determine an appropriate sample size for future validation studies. 

The error of thefirst kind is also termed a error, type I error, or rejection error. Other names for the error of the second kind are p error, type II error, or acceptance error. 

Figure 2.1 la illustrates the relationship between the error of the first kind, also called a error, and the error of the second kind P error) for the comparison of two means. An error of the first kind is that the means are taken to be different, although they deviate from each other randomly. The error of the second kind is that it is wrongly stated that the two means are comparable. 

A shift of the critical values to lower a values is related to an increase in the p error. A simultaneous decrease in the a and P errors is only feasible If the number of measurements, n, is increased. Since the width of the distribution is proportional to al fn, a larger number of measurements leads obviously to a narrower distribution (cf. Figure 2.11b). 

Spafh, P, Error Reduction in Health Care A Systems Approach to Improving Patient Safety, AHA Press, Chicago, 2000. 

Stainton, M.P., Errors in molybdenum blue methods determining orthophosphate in fresh-waters, Canadian Journal of Fisheries and Aquatic Science 37, 472,1980. 

To take into account the p error we must have resource to the new definition of the LOD CCp, the capability of detection " (as denoted by the EU) or minimum detectaljle net concentration, (as ISO termed it). This is the true analyte concentration that leads to a correct positive detection decision with sufficiently high probability (1 — jS). In other words, it is the minimum concentration of analyte that can be discriminated from the blank, controlling the risks of false positives and false negatives. 

We wish to detect an increase from an estimated 20 100,000 births to 30 100,000 births. If we accept a Type II (P) error of 0.20, this requires at the 0.05 level 365,000 person determinations in each sample or, at the 0.01 level, 592,000 person determinations. 

From an observed frequency of 20 100,000 births to 30 100,000 births, at the indicated probability levels for type I (a) and type II (P) errors. The t values are based on one-tailed probability distributions. 

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