Variables, designation

Basically, the tabled values represent area (proportions or probability) associated with a scaling variable designated by Z in Fig. 3-56. The normal cui ve is centered at 0, and for particular values of Z, designated as z, the tabulated numbers represent the corresponding area under the cui ve between 0 and z. For example, between 0 and 1 the area is. 3413. (Get this number from Table 3-4. The value of A includes the area on both sides of zero. Thus we want A/2. For z = 1, A = 0.6827, A/2 = 0.3413. For z = 2, A/2 = 0.4772.) The area between... 

Process measurements encompass the apphcation of the principles of metrology to the process in question. The objective is to obtain values for the current conditions within the process and make this information available in a form usable by either the control system, process operators, or any other entity that needs to know The term measured variable or process variable designates the process condition that is being determined. 

How the number of process variables, design relationships, and design variables defines a system can be best illustrated by considering the simplest system a single-phase, process stream. 

Once an output set has been established, the direction of information flow is fixed in the system of equations, and they can be represented either by a linear diagraph or its associated Boolean adjacency matrix. For our purposes it is more convenient to work with the Boolean adjacency matrix, which can be obtained directly from the occurrence matrix and output set as follows. First, assign numbers to the equations that correspond to the rows, and numbers to the variables that correspond to the columns of the occurrence matrix as in Fig. 5. Then pick an output set by the methods described in Section III. For the first equation, and the number of the column containing its output variable. The information flow transmitted by the variable designated by the column number goes to all other equations that have nonzero... 

Monitoring statistics starts with a random variable design to find and describe a toxic chemical site by a mean and a variance. 

C.A.A. Duineveld, Construction and analysis of mixture-process variables designs as applied to tablet formulations, Ph.D. Thesis, 1993, University of Groningen, Netherlands. 

Fixed effects -among experimental variables [DESIGN OF EXPERIMENTS] (Vol 7)... 

Transmitter span Manipulated variable Design value Maximum flow... 

Boston, J. F., "Algorithms for Distillation Calculations with Bounded-Variable Design Constraints and Equality-or Inequality-Constrained Optimization", Paper presented at Houston AIChE Meeting, April 1979. 

Table 2.15 Leverage for three possible single variable designs using a two parameter linear model.

Linear programming is concerned with solutions to simultaneous linear equations where the equations are developed on the basis of restrictions on the variables. Because these restrictions are often expressed as inequalities, it is necessary to convert these inequalities to equalities. This can be accomplished by the inclusion of a new variable designated as a slack variable. 

Thus, if T is normally distributed with mean n and standard deviation a, then the random variable, (T — /i)/<7, is also normally distributed with mean 0 and standard deviation 1. The term (T — ix)/a is called a standard normal variable (designated by Z) and the graph of its PDF is called a standard normal curve. The literature provides a tabulation of areas under a standard normal curve to the right of Zq for nonnegative values of Zq. From these tables, probabilities about a standard normal variable, Z, can be determined. (See Chapter 52 for additional details.)... 

Let X(t) be a random variable designating the number of events occurring during the time interval (0, t). An interesting question regarding to the random variable X(t) may be presented as what is the probability that the number of events occurring during the time interval (0, t) = t will be equal to some prescribed value X. Mathematically it is presented by ... 

X(t) is a random variable designating the population size at time t ... 

The g functions (Equation 4.3) that define the column performance may be general functions of the primary variables designed to meet special separation specifications, or they may directly specify the values of the primary variables. Combinations of different types of specifications are possible. 

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