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Standard deviation limits

The material selected for the pin was 070M20 normalized mild steel. The pin was to be manufactured by machining from bar and was assumed to have non-critical dimensional variation in terms of the stress distribution, and therefore the overload stress could be represented by a unique value. The pin size would be determined based on the —3 standard deviation limit of the material s endurance strength in shear. This infers that the probability of failure of the con-rod system due to fatigue would be very low, around 1350 ppm assuming a Normal distribution for the endurance strength in shear. This relates to a reliability R a 0.999 which is adequate for the... [Pg.245]

The minimum enduranee strength for the problem stated earlier is set at the —3 standard deviations limit, therefore ... [Pg.247]

Compounds Matrix Extraction technique Recovery (%) Relative standard deviation (%) Limit of detection (ng g-1)11 Reference... [Pg.446]

Figure 4. Graph of Pt-P length (shown with standard deviation limits) against 2]pt-p for platinum(II) complexes of trialkylphosphines , phosphorus trans to phosphorus , phosphorus trans to chlorine , phosphorus trans to other donor atoms O, trans-[Ptl2(PCy3)2], For discussion see Ref. 23 the point with JPt-P > 5000 Hz is for [Pt2(p-Cl)2(COEt)2(PMe2Ph)2] (24). Some platinum(IV) complexes have been... Figure 4. Graph of Pt-P length (shown with standard deviation limits) against 2]pt-p for platinum(II) complexes of trialkylphosphines , phosphorus trans to phosphorus , phosphorus trans to chlorine , phosphorus trans to other donor atoms O, trans-[Ptl2(PCy3)2], For discussion see Ref. 23 the point with JPt-P > 5000 Hz is for [Pt2(p-Cl)2(COEt)2(PMe2Ph)2] (24). Some platinum(IV) complexes have been...
Figure 2 and listed in Table II for the time course of 7 days of storage with standard deviation limits for FPD responses of the three sulfur markers. [Pg.456]

The Clog P values of 228 structures (1.8% of the data set) were not well predicted. It must be noted that Starlist (most accurate values in the database) contains almost 300 charged nitrogen solutes (ammonium, pyri-dinium, imidazolium, etc.) and over 2200 in all, which amounts to 5% of Masterfile (database of measured values). CLOGP adequately handles these molecules within the 0.30 standard deviation limit. Most other programs make no attempt to calculate them. For more details on calculating logfrom structures, see excellent reviews by Leo (140,141). [Pg.18]

Figure 4 Bootstrap standard deviation plot exhibiting the possibility for qualitative identification of polymer film coating endpoint. Dashed line indicates the three-standard deviation limit for spectral similarity. Near-IR spectra from 10 samples obtained at the 16% theoretical applied solids level were used as a training group. Figure 4 Bootstrap standard deviation plot exhibiting the possibility for qualitative identification of polymer film coating endpoint. Dashed line indicates the three-standard deviation limit for spectral similarity. Near-IR spectra from 10 samples obtained at the 16% theoretical applied solids level were used as a training group.
For the dry and shaded control experiment (Plot D - Shaded) the surface scraping sample concentration falls within the 2 standard deviation limits about the mean. This implies that no statistically significant loss of TCDD occurred in the dry shaded plot. Therefore, the presence of water and/or sunlight are important environmental parameters affecting the mobility of TCDD in soils. [Pg.125]

The laboratory should maintain a continuing quality control chart (Figure 3.6) for each method. A reference material of known analyte content is blindly and randomly run each day, or preferably with each batch of samples. If measured values fall outside prescribed standard deviation limits, then you should check for some systematic error such as reagent deterioration or instrument drift (needs recalibration). [Pg.133]

Where the single-sample bootstrap algorithm provides for the qualitative analysis of a single test sample, the modified bootstrap algorithm [14] provides a test that uses multiple test spectra to detect false samples (as subclusters) well within the three-standard deviation limit of a training set. The accurate detection of subclusters allows the determination of very small changes in component concentration or physical attributes. [Pg.41]

Figure 4.31 Illustration of hypothesis that colloidal association interferes with the measurement of the antibacterial activity of ABDAC s in a MIC test ( ) CMC measured in deionized distilled water ( ) MIC values in CDM and the standard deviations (—) limiting solubility of the monomeric form of the quaternaries in CDM (i.e. critical micelle concentration in CDM) (- - - -) extrapolated line of the C8-C14 activity data of the ABDAC s. Shaded portion represents the amount of monomer required to be released from the micellar state before an effective equilibrium concentration is reached. From [212]. Figure 4.31 Illustration of hypothesis that colloidal association interferes with the measurement of the antibacterial activity of ABDAC s in a MIC test ( ) CMC measured in deionized distilled water ( ) MIC values in CDM and the standard deviations (—) limiting solubility of the monomeric form of the quaternaries in CDM (i.e. critical micelle concentration in CDM) (- - - -) extrapolated line of the C8-C14 activity data of the ABDAC s. Shaded portion represents the amount of monomer required to be released from the micellar state before an effective equilibrium concentration is reached. From [212].

See other pages where Standard deviation limits is mentioned: [Pg.226]    [Pg.398]    [Pg.250]    [Pg.124]    [Pg.47]    [Pg.274]    [Pg.106]    [Pg.273]    [Pg.121]    [Pg.125]    [Pg.434]    [Pg.608]    [Pg.80]    [Pg.452]    [Pg.320]    [Pg.320]    [Pg.206]    [Pg.2401]   
See also in sourсe #XX -- [ Pg.77 ]




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