Variability causes

What two variables cause the boiling points of substances to be different ... 

The reliability of multispecies analysis has to be validated according to the usual criteria selectivity, accuracy (trueness) and precision, confidence and prediction intervals and, calculated from these, multivariate critical values and limits of detection. In multivariate calibration collinearities of variables caused by correlated concentrations in calibration samples should be avoided. Therefore, the composition of the calibration mixtures should not be varied randomly but by principles of experimental design (Deming and Morgan [1993] Morgan [1991]). 

PCA is successful for data sets with correlating variables as it is often the case with data from chemistry. Constant variables or highly correlating variables cause no problems for PCA however, outliers may have a severe influence on the result, and also scaling is important. 

Scaling of the data sometimes has an undesirable effect, because each variable will get the same weight for PCA. Thus, variables which are known to include essentially noise will become as important as variables which reflect the true signal. PCA cannot distinguish between important and unimportant information (variance), it will try to express as much of the data variability as possible—also the variability caused by noise. In such cases, the data should not be scaled in order to keep the original importance of the variables. 

Electrokinetic injection is useful when the analyte is in the presence of interfering species (with different mobilities), qualitative applications, or when viscous buffers or gels are being used. It is usually not suitable for quantitative applications since the variability caused by conductivity, microenvironments, and matrix differences significantly reduces the reproducibility. Since sample depletion can be a significant issue, it is recommended that different samples are used when repeated injections are needed. 

A scatter diagram shows how two variables are related and is thus used to test for cause and effect relationships. It cannot prove that one variable causes the change in the other, only that a relationship exists and how strong it is. In a scatter diagram, the horizontal (x) axis represents the measurement values of one variable, and the vertical (y) axis represents the measurements of the second variable. 

Work hard to control the patient-to-patient variability, which not only depends on in-built patient differences, but also on extraneous variability caused by an inconsistent measurement technique, data recording and sloppy methodology. Tightening up on these things will over time bring a down and help to keep sample sizes lower than they would otherwise be. 

Variables can often be altered simultaneously, this makes it impossible to later determine which variable caused a given effect. This is known as semi-confounding of effects. 

An efficient representation of complex relationships between many process and formulation variables (causes), and a single response (effect) can be shown by using a cause-and-effect diagram [1], Figure 4 is a simple example. 

Person to person variability caused by differences in tongue movements, saliva amounts, and saliva content... 

Thus it would seem that there are unusual features in this system which might make it particularly sensitive to the choices of some bond parameters, and that there are difficulties in assigning reasonable values to some bonds. Thus the variability caused by these features might be peculiar to this system. In all other respects, however, there is no reason to expect excessive variability the converse is a more likely expectation. 

Regarding the influence of the target ion concentration on the SWV curves, the major difference found between systems with one or two polarized interfaces is that this variable causes a shift of the peak potentials toward more anodic values through an increase of E 2 in the latter case (see Eqs. (7.41)—(7.43)), whereas only an increase in the peak current is observed for systems with one polarized interface [36]. Therefore, SWV is a very good analytical tool for the determination of ion concentrations in both kinds of membrane systems. 

To retain some information furnished by animal models, but reduce the variability caused by whole animal models, many workers have resorted to excised tissue preparations. Classical preparations include excised rat gut... 

In general, calculations of industrial emissions rely on default values according to the industrial sector, emission rates, wind velocity and direction, anticipated substance flows through the environment, abatement technologies and wastewater treatment processes (see [114]). Site-specific assessments and local environmental exposure assessments must also account for geographic variability caused by climate, hydrology, geology, and biotic conditions [115]. 

As discussed earlier, water has a direct influence on the resistance of microorganisms to dry-heat destruction. The destruction rate of spores is a function of the quantity of water in the cell at the time of heating. This water content is only constant under certain conditions and in most conditions, the moisture content of the cell can change so that the secondary variables cause confusion in analysis of results. The water vapor pressure in the atmosphere surrounding the cell determines the movement of water to or from microorganisms on surfaces. Research found that when the humidity in air passing over spores was increased from 0-0.2, the D value also increased by a factor of 100. Spores of intermediate moisture content with an RH between 0.1 and... 

Burger DM, Siebers MC, Hugen PW, Aarnoutse RE, Hekster YA, Koopmans PP. Pharmacokinetic variability caused by gender do women have higher indinavir exposure than men J Acquir Immune Defic Syndr 2002 29(l) 101-2. 

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