Concentration standard deviation

Gulson et al. (1998) used measured lead isotope ratios (207Pb/206Pb and 206Pb/204Pb) in mothers breast milk and in infants blood to establish that, for the first 60-90 days postpartum, the contribution from breast milk to blood lead in the infants varied from 36% to 80%. Maternal bone and diet appear to be the major sources of lead in breast milk. Mean lead concentration ( standard deviation) in breast milk for participants in the study was 0.73 0.70 pg/kg. 

Several investigators reported the presence of nickel concentrations in rain. The annual mean nickel concentration in precipitation at Lewes, Delaware, was 0.79 pg/L (Barrie et al. 1987). The mean concentration ( standard deviation) of nickel collected from rain showers in southern Ontario, Canada, in 1982 was 0.56 0.07 pg/L (Chan et al. 1986). The mean concentrations in northern and central Ontario were both 0.61 pg/L, indicating a lack of spatial variability. Sudbury, the site of a large nickel smelter, is located in central Ontario. Nickel concentrations from rain samples collected at four sites in Sweden had a mean range of 0.017-0.51 pg/L (Hansson et al 1988). 

Hydrocarbons in the cab of an automobile were measured during trips on the New Jersey Turnpike and trips through the Lincoln Tunnel connecting New York and New Jersey.14 The total concentrations ( standard deviations) of m- and p-xylene were... 

Uranium Isotope Average Concentration Standard Deviation... 

Table 6.8. Metal concentrations (+ standard deviation) in surface freshwater sediments ...

Martin, D. O. (1976) Comment on the change of concentration standard deviations with distance, J. Air Pollut. Control Assoc. 26, 145-146. 

Find the mean concentration, standard deviation, and the coefficient of variation (%) of the fortified samples. 

When at least three samples (preferably more) with known concentrations (standards) are analyzed at each concentration, standard deviations can be calculated from the peak areas (external standard and standard addition methods) or peak area ratios (internal standard method), thereby determining the confidence of data for unknown concentrations. The standard deviations are usually plotted as error bars at each point on the calibration graphs. 

D.1 Simultaneous Laminar Mixing and Diffusion. Consider the case of a cubic element of the minor component (10% by volume) which is simultaneously subjected to laminar mixing and diffusion (Fig. 6.37). The minor component diffuses into the major and the thickness of the cubic element is reduced as the interface in the yz plane increases. Calculate the time necessary for the minor component to diffuse into the major component so that the concentration standard deviation is 0.11. D- = 10 ° emVs, To = 3 mm, and y = 50 s . Compare this time to the corresponding time without shearing. 

TEST FOR CONCENTRATED SOURCES THRESHOLD VALUE ON STANDARD DEVIATION (intNa). SCREEN ALL SOURCES WHOSE COUNTS ARB BELOW THRESHOLD... 

The scatter of the points around the calibration line or random errors are of importance since the best-fit line will be used to estimate the concentration of test samples by interpolation. The method used to calculate the random errors in the values for the slope and intercept is now considered. We must first calculate the standard deviation Sy/x, which is given by ... 

The detection limits in the table correspond generally to the concentration of an element required to give a net signal equal to three times the standard deviation of the noise (background) in accordance with lUPAC recommendations. Detection limits can be confusing when steady-state techniques such as flame atomic emission or absorption, and plasma atomic emission or fluorescence, which... 

The detection limits in the table correspond generally to the concentration of analyte required to give a net signal equal to three times the standard deviation of the background in accordance with lUPAC recommendations. 

There is a temptation when analyzing data to plug numbers into an equation, carry out the calculation, and report the result. This is never a good idea, and you should develop the habit of constantly reviewing and evaluating your data. For example, if analyzing five samples gives an analyte s mean concentration as 0.67 ppm with a standard deviation of 0.64 ppm, then the 95% confidence interval is... 

This confidence interval states that the analyte s true concentration lies within the range of -0.16 ppm to 1.44 ppm. Including a negative concentration within the confidence interval should lead you to reevaluate your data or conclusions. On further investigation your data may show that the standard deviation is larger than expected. 

To calculate the standard deviation for the analyte s concentration, we must determine the values for y and E(x - x). The former is just the average signal for the standards used to construct the calibration curve. From the data in Table 5.1, we easily calculate that y is 30.385. Calculating E(x - x) looks formidable, but we can simplify the calculation by recognizing that this sum of squares term is simply the numerator in a standard deviation equation thus,... 

Few populations, however, meet the conditions for a true binomial distribution. Real populations normally contain more than two types of particles, with the analyte present at several levels of concentration. Nevertheless, many well-mixed populations, in which the population s composition is homogeneous on the scale at which we sample, approximate binomial sampling statistics. Under these conditions the following relationship between the mass of a randomly collected grab sample, m, and the percent relative standard deviation for sampling, R, is often valid. ... 

This short paper describes a demonstration suitable for use in the classroom. Two populations of corks are sampled to determine the concentration of labeled corks. The exercise demonstrates how increasing the number of particles sampled improves the standard deviation due to sampling. 

Precision For absorbances greater than 0.1-0.2, the relative standard deviation for atomic absorption is 0.3-1% for flame atomization, and 1-5% for electrothermal atomization. The principal limitation is the variation in the concentration of free-analyte atoms resulting from a nonuniform rate of aspiration, nebulization, and atomization in flame atomizers, and the consistency with which the sample is heated during electrothermal atomization. 

Precision When the analyte s concentration is well above the detection limit, the relative standard deviation for fluorescence is usually 0.5-2%. The limiting instrumental factor affecting precision is the stability of the excitation source. The precision for phosphorescence is often limited by reproducibility in preparing samples for analysis, with relative standard deviations of 5-10% being common. 

Precision For samples and standards in which the concentration of analyte exceeds the detection limit by at least a factor of 50, the relative standard deviation for both flame and plasma emission is about 1-5%. Perhaps the most important factor affecting precision is the stability of the flame s or plasma s temperature. For example, in a 2500 K flame a temperature fluctuation of +2.5 K gives a relative standard deviation of 1% in emission intensity. Significant improvements in precision may be realized when using internal standards. 

Single-operator characteristics are determined by analyzing a sample whose concentration of analyte is known to the analyst. The second step in verifying a method is the blind analysis of standard samples where the analyte s concentration remains unknown to the analyst. The standard sample is analyzed several times, and the average concentration of the analyte is determined. This value should be within three, and preferably two standard deviations (as determined from the single-operator characteristics) of the analyte s known concentration. 

I which, for an average recovery of 98.1% gives a relative standard deviation of approximately 0.7%. If the acid s concentration is controlled such that its effect approaches that for factors B, C, and F, then the relative standard deviation becomes 0.18, or approximately 0.2%. 

What is the estimated relative standard deviation for the results of a collaborative study in which the sample is pure analyte (100% w/w analyte) Repeat for the case in which the analyte s concentration is 0.1% w/w. 

Thus, we expect that approximately 67% of the participants in the collaborative study (+I0) will report the analyte s concentration within the range of 98% w/w to 102% w/w. When the analyte s concentration is 0.1% w/w (C = 0.001), the estimated percent relative standard deviation is... 

Compound Sample concentration, ppm Recovery, % Standard deviation... 

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. 

This solution describes a plume with a Gaussian distribution of poUutant concentrations, such as that in Figure 5, where (y (x) and (y (x) are the standard deviations of the mean concentration in thejy and directions. The standard deviations are the directional diffusion parameters, and are assumed to be related simply to the turbulent diffusivities, and K. In practice, Ct (A) and (y (x) are functions of x, U, and atmospheric stability (2,31—33). 

Fig. 5. Diffusion of pollutants from a point source. PoUutant concentrations have separate Gaussian distributions in both the horizontal (j) and vertical directions. The spread is parameterized by the standard deviations ( O ) which are related to the diffusivity (fQ.

Assay Concentration, ppm Standard deviation, ppm Number of samples... 

E. Solid particles with significant density difference Ns, = = 2 + 0.44( YnV" [E] Use log mean concentration difference. Nsi, standard deviation 11.1%. i>sijp calculated by methods given in reference. [118]... 

Blend time tb, the time required to achieve a specified maximum standard deviation of concentration after injection of a tracer into a stirred tank, is made dimensionless by multipfying by the impeller rotational speed ... 

Sutton Micrometeorology, McGraw-Hill, 1953, p, 286) developed a solution to the above difficulty by defining dispersion coefficients, O, Gy, and O, defined as the standard deviation of the concentrations in the downwind, crosswind, and vertical x, y, z) directions, respectively, The dispersion coefficients are a function of atmospheric conditions and the distance downwind from the release. The atmospheric conditions are classified into six stability classes (A through F) for continuous releases and three stability classes (unstable, neutral, and stable) for instantaneous releases. The stability classes depend on wind speed and the amount of sunlight, as shown in Table 26-28,... 

ICP-SFMS (Thermo Finnigan, Flement) with cold vapour generation was developed with a guard electrode and a gold amalgamation device using an Au-sorbent for sample pre-concentration to improve the sensitivity. Instrumental parameters of ICP-SFMS such as take-up time, heating temperature of Au-sorbent, additional gas flow, and sample gas flow were optimized. Detection limit calculated as 3 times the standard deviation of 10 blanks was 0,05 ng/1, RSD = 7-9 %. 

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