 10.2.1: Show that the methodofmoments estimators of the population mean a...
 10.2.2: Consider the problem of deriving methodofmoments estimates for th...
 10.2.3: The memory residence times of 13,171 jobs were measured, and the sa...
 10.2.4: Show that methodofmoments estimates for the parameters 1 and 2 of...
Solutions for Chapter 10.2: Parameter Estimation
Full solutions for Probability and Statistics with Reliability, Queuing, and Computer Science Applications  2nd Edition
ISBN: 9781119285427
Solutions for Chapter 10.2: Parameter Estimation
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. Probability and Statistics with Reliability, Queuing, and Computer Science Applications was written by Patricia and is associated to the ISBN: 9781119285427. This textbook survival guide was created for the textbook: Probability and Statistics with Reliability, Queuing, and Computer Science Applications , edition: 2. Chapter 10.2: Parameter Estimation includes 4 full stepbystep solutions. Since 4 problems in chapter 10.2: Parameter Estimation have been answered, more than 1076 students have viewed full stepbystep solutions from this chapter.

`error (or `risk)
In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).

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.

Attribute control chart
Any control chart for a discrete random variable. See Variables control chart.

Bayesâ€™ estimator
An estimator for a parameter obtained from a Bayesian method that uses a prior distribution for the parameter along with the conditional distribution of the data given the parameter to obtain the posterior distribution of the parameter. The estimator is obtained from the posterior distribution.

Bimodal distribution.
A distribution with two modes

Chisquare test
Any test of signiicance based on the chisquare distribution. The most common chisquare tests are (1) testing hypotheses about the variance or standard deviation of a normal distribution and (2) testing goodness of it of a theoretical distribution to sample data

Components of variance
The individual components of the total variance that are attributable to speciic sources. This usually refers to the individual variance components arising from a random or mixed model analysis of variance.

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

Contingency table.
A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria

Control limits
See Control chart.

Cumulative sum control chart (CUSUM)
A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t

Discrete distribution
A probability distribution for a discrete random variable

Discrete random variable
A random variable with a inite (or countably ininite) range.

Enumerative study
A study in which a sample from a population is used to make inference to the population. See Analytic study

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.

Exhaustive
A property of a collection of events that indicates that their union equals the sample space.

Exponential random variable
A series of tests in which changes are made to the system under study

Ftest
Any test of signiicance involving the F distribution. The most common Ftests are (1) testing hypotheses about the variances or standard deviations of two independent normal distributions, (2) testing hypotheses about treatment means or variance components in the analysis of variance, and (3) testing signiicance of regression or tests on subsets of parameters in a regression model.

Fixed factor (or fixed effect).
In analysis of variance, a factor or effect is considered ixed if all the levels of interest for that factor are included in the experiment. Conclusions are then valid about this set of levels only, although when the factor is quantitative, it is customary to it a model to the data for interpolating between these levels.

Generating function
A function that is used to determine properties of the probability distribution of a random variable. See Momentgenerating function
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