 8.6.1.2.1: Show that the matrix Q defined by equation (8.133) is a DTMC matrix.
 8.6.1.2.2: Show that with condition (8.135), Q is an aperiodic matrix.
 8.6.1.2.3: Perform steadystate analysis of the CTMC model in Example 8.23 (Fi...
 8.6.1.2.4: Apply the power method to the CTMC of Figure 8.P.4 to obtain an exp...
 8.6.1.2.5: Suppose that we are interested in computing the derivative d/d with...
 8.6.1.2.6: Show that the GaussSeidel iteration matrix for the CTMC of Figure 8...
Solutions for Chapter 8.6.1.2: Successive Overrelaxation (SOR).
Full solutions for Probability and Statistics with Reliability, Queuing, and Computer Science Applications  2nd Edition
ISBN: 9781119285427
Solutions for Chapter 8.6.1.2: Successive Overrelaxation (SOR).
Get Full SolutionsChapter 8.6.1.2: Successive Overrelaxation (SOR). includes 6 full stepbystep solutions. This textbook survival guide was created for the textbook: Probability and Statistics with Reliability, Queuing, and Computer Science Applications , edition: 2. Probability and Statistics with Reliability, Queuing, and Computer Science Applications was written by and is associated to the ISBN: 9781119285427. This expansive textbook survival guide covers the following chapters and their solutions. Since 6 problems in chapter 8.6.1.2: Successive Overrelaxation (SOR). have been answered, more than 2965 students have viewed full stepbystep solutions from this chapter.

Alternative hypothesis
In statistical hypothesis testing, this is a hypothesis other than the one that is being tested. The alternative hypothesis contains feasible conditions, whereas the null hypothesis speciies conditions that are under test

Analysis of variance (ANOVA)
A method of decomposing the total variability in a set of observations, as measured by the sum of the squares of these observations from their average, into component sums of squares that are associated with speciic deined sources of variation

Assignable cause
The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.

Average
See Arithmetic mean.

Axioms of probability
A set of rules that probabilities deined on a sample space must follow. See Probability

Backward elimination
A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

Bimodal distribution.
A distribution with two modes

C chart
An attribute control chart that plots the total number of defects per unit in a subgroup. Similar to a defectsperunit or U chart.

Center line
A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.

Chance cause
The portion of the variability in a set of observations that is due to only random forces and which cannot be traced to speciic sources, such as operators, materials, or equipment. Also called a common cause.

Coeficient of determination
See R 2 .

Conditional variance.
The variance of the conditional probability distribution of a random variable.

Contrast
A linear function of treatment means with coeficients that total zero. A contrast is a summary of treatment means that is of interest in an experiment.

Control limits
See Control chart.

Density function
Another name for a probability density function

Distribution function
Another name for a cumulative distribution function.

Error propagation
An analysis of how the variance of the random variable that represents that output of a system depends on the variances of the inputs. A formula exists when the output is a linear function of the inputs and the formula is simpliied if the inputs are assumed to be independent.

Finite population correction factor
A term in the formula for the variance of a hypergeometric random variable.

Fractional factorial experiment
A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.

Harmonic mean
The harmonic mean of a set of data values is the reciprocal of the arithmetic mean of the reciprocals of the data values; that is, h n x i n i = ? ? ? ? ? = ? ? 1 1 1 1 g .