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Products standard deviation

Mean heat production. Standard deviation on the heat produetion distribution. Number of sites. Analyses were made on mixed powders, implying that the standard deviation of the analyses underestimates the true spread of values for individual rock samples. Average calculated by weighting according to the abundances of the different rock types. Baltic Shield data compiled from Hanski (1992), Eilu (1994),... [Pg.1334]

The combined result of two such determinations yielded a leak size figure of 8.8% of the feed flow (with a relative standard deviation of less than 5%). This figure could sufficiently explain the product quality problems experienced, whose alternative explanation in turn was catalyst poisoning. [Pg.1059]

Control charts were originally developed in the 1920s as a quality assurance tool for the control of manufactured products.Two types of control charts are commonly used in quality assurance a property control chart in which results for single measurements, or the means for several replicate measurements, are plotted sequentially and a precision control chart in which ranges or standard deviations are plotted sequentially. In either case, the control chart consists of a line representing the mean value for the measured property or the precision, and two or more boundary lines whose positions are determined by the precision of the measurement process. The position of the data points about the boundary lines determines whether the system is in statistical control. [Pg.714]

A study was conducted to measure the concentration of D-fenfluramine HCl (desired product) and L-fenfluramine HCl (enantiomeric impurity) in the final pharmaceutical product, in the possible presence of its isomeric variants (57). Sensitivity, stabiUty, and specificity were enhanced by derivatizing the analyte with 3,5-dinitrophenylisocyanate using a Pirkle chiral recognition approach. Analysis of the caUbration curve data and quaUty assurance samples showed an overall assay precision of 1.78 and 2.52%, for D-fenfluramine HCl and L-fenfluramine, with an overall intra-assay precision of 4.75 and 3.67%, respectively. The minimum quantitation limit was 50 ng/mL, having a minimum signal-to-noise ratio of 10, with relative standard deviations of 2.39 and 3.62% for D-fenfluramine and L-fenfluramine. [Pg.245]

Assume that the table represents typical production-hne performance. The numbers themselves have been generated on a computer and represent random obseiwations from a population with I = 3.5 and a population standard deviation <7 = 2.45. The sample values reflect the way in which tensile strength can vary by chance alone. In practice, a production supervisor unschooled in statistics but interested in high tensile performance would be despondent on the eighth day and exuberant on the twentieth day. If the supeiwisor were more concerned with uniformity, the lowest and highest points would have been on the eleventh and seventeenth days. [Pg.490]

Figure 7 The production and emission of NO during denitrification in agricultural soil treated with NO3 fertilizer (KNO3) and the nitrification inhibitor Dyciandiamide (10%) under aerobic (air) and anerobic conditions (N,). Fluxes are means from three soil columns, error bars represent standard deviations from the mean. V = vertical flow through the column H = Horizontal flow over the soil surface. Figure 7 The production and emission of NO during denitrification in agricultural soil treated with NO3 fertilizer (KNO3) and the nitrification inhibitor Dyciandiamide (10%) under aerobic (air) and anerobic conditions (N,). Fluxes are means from three soil columns, error bars represent standard deviations from the mean. V = vertical flow through the column H = Horizontal flow over the soil surface.
On Figure 6.3.1 the first line tells the date and duration of the experiment. In the third line the number of cycles is five. This indicates that feed and product streams were analyzed five times before an evaluation was made. The concentrations, and all other numbers are the average of the five repeated analyses with the standard deviation given for each average value. The RATE as 1/M means for each component the reaction rate in lb-moles per 1000 lbs of catalyst. [Pg.126]

As can be seen from the above equations, the standard deviation of the strength increases significantly with the number of processes used in manufacture that are adding the residual stresses. This may be the reason for the apparent reluctance of suppliers to give precise statistical data about their product (Carter, 1997). [Pg.162]

The in equation 4.19 relates to the fact that this is not the true standard deviation, but an estimate to measure the process shift (or drift) in the distribution over the expected duration of production. Equation 4.20 is the best estimate for the standard deviation of the distribution as determined by CA with no process shift. [Pg.163]

For the solenoid dimensions, D, r and d, we can use Conformability Analysis (CA) to predict the standard deviations based on a shifted distribution, a, which provides the largest estimate (or worst case) anticipated during a production run. Given that the dimension Z) = 012 0.03 mm is turned, the material to process risk can be shown to be = 1.2, and the geometry to process risk, g = 1. An adjusted tolerance is then given by ... [Pg.206]

The configuration of the product in terms of its design standard, deviations, nonconformities, and design changes to be recorded prior to and subsequent to the tests... [Pg.267]

Various novel applications in biotechnology, biomedical engineering, information industry, and microelectronics involve the use of polymeric microspheres with controlled size and surface properties [1-31. Traditionally, the polymer microspheres larger than 100 /urn with a certain size distribution have been produced by the suspension polymerization process, where the monomer droplets are broken into micron-size in the existence of a stabilizer and are subsequently polymerized within a continuous medium by using an oil-soluble initiator. Suspension polymerization is usually preferred for the production of polymeric particles in the size range of 50-1000 /Ltm. But, there is a wide size distribution in the product due to the inherent size distribution of the mechanical homogenization and due to the coalescence problem. The size distribution is measured with the standard deviation or the coefficient of variation (CV) and the suspension polymerization provides polymeric microspheres with CVs varying from 15-30%. [Pg.189]

Over the range of 100 to 600 mA cm"2, the current efficiency for the production of hydrogen was 100%, with a standard deviation of 2%. Over the range of 100 to 600 mA cm-2, the current efficiency for the production of fluorine was 100% with a standard deviation of 2%. Essentially the same results were obtained with helium reference flows. [Pg.536]

To illustrate this, we shall start with 2500 A ingredients and set the transition probabilities to Pi (A B) = 0.01, Pi (B A) = 0.02, Pi (A C) = 0.001, and Pi (C A) = 0.0005. Note that these values yield a situation favoring rapid initial transition to species B, since the transition probability for A B is 10 times than that for A C. However, the formal equilibrium constant eq[C]/[A] is 2.0, whereas eq[B]/[A] = 0.5, so that eventually, after the establishment of equilibrium, product C should predominate over product B. This study illustrates the contrast between the short run (kinetic) and the long run (thermodynamic) aspects of a reaction. To see the results, plot the evolution of the numbers of A, B, and C cells against time for a 10,000 iteration run. Determine the average concentrations [A]avg, [B]avg, and [C]avg under equilibrium conditions, along with their standard deviations. Also, determine the iteration Bmax at which ingredient B reaches its maximum value. [Pg.121]

Note that in data analysis we divide by n in the definition of standard deviation rather than by the factor n - 1 which is customary in statistical inference. Likewise we can relate the product-moment (or Pearson) coefficient of correlation r (Section 8.3.1) to the scalar product of the vectors (x - x) and (y - y) ... [Pg.14]

In these cases it is not necessary to determine the absolute bioavailability or the absorption rate constant for the product under study. It is only necessary to prove that the plasma concentration versus time curve is not significantly different from the reference product s curve. This is done by comparing the means and standard deviations of the plasma concentrations for the two products at each sampling time using an appropriate statistical test. [Pg.96]

According to Eq.(4.27a,b), the covariance is composed of the product of the standard deviations or uncertainties, respectively, of the parameters pi and pj and the correlation coefficient between them ... [Pg.103]

Chi-Square Distribution For some industrial applications, product uniformity is of primary importance. The sample standard deviation s is most often used to characterize uniformity. In dealing with this problem, the chi-square distribution can be used where %2 = s2/a2) (df). The chi-square distribution is a family of distributions which are defined by the degrees of freedom associated with the sample variance. For most applications, df is equal to the sample size minus 1. [Pg.76]

Niclosamide and its dosage forms were spectrophotometrically estimated by reaction with aqueous 4-aminophenazone in the presence of ammonia and measurement of absorbance of the resulting oxidative coupling product at 520 nm [50], Beer s law was obeyed in the concentration range 1.25-10.0 pg/mL the relative standard deviation was 1.51% and the recovery 98.9 99.6%. Dosage form excipients did not interfere. [Pg.85]


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See also in sourсe #XX -- [ Pg.128 , Pg.129 ]




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