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Solutions for Chapter 3.2.3.3: The Exponential Contribution

Probability and Statistics with Reliability, Queuing, and Computer Science Applications | 2nd Edition | ISBN: 9781119285427 | Authors: Kishor S. Trivedi

Full solutions for Probability and Statistics with Reliability, Queuing, and Computer Science Applications | 2nd Edition

ISBN: 9781119285427

Probability and Statistics with Reliability, Queuing, and Computer Science Applications | 2nd Edition | ISBN: 9781119285427 | Authors: Kishor S. Trivedi

Solutions for Chapter 3.2.3.3: The Exponential Contribution

Solutions for Chapter 3.2.3.3
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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 Patricia and is associated to the ISBN: 9781119285427. Since 1 problems in chapter 3.2.3.3: The Exponential Contribution have been answered, more than 1023 students have viewed full step-by-step solutions from this chapter. Chapter 3.2.3.3: The Exponential Contribution includes 1 full step-by-step solutions. This expansive textbook survival guide covers the following chapters and their solutions.

Key Statistics Terms and definitions covered in this textbook
  • `-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).

  • Axioms of probability

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

  • Bayes’ 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.

  • Bernoulli trials

    Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

  • C chart

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

  • Conidence interval

    If it is possible to write a probability statement of the form PL U ( ) ? ? ? ? = ?1 where L and U are functions of only the sample data and ? is a parameter, then the interval between L and U is called a conidence interval (or a 100 1( )% ? ? conidence interval). The interpretation is that a statement that the parameter ? lies in this interval will be true 100 1( )% ? ? of the times that such a statement is made

  • Continuous distribution

    A probability distribution for a continuous random variable.

  • Continuous random variable.

    A random variable with an interval (either inite or ininite) of real numbers for its range.

  • Cook’s distance

    In regression, Cook’s distance is a measure of the inluence of each individual observation on the estimates of the regression model parameters. It expresses the distance that the vector of model parameter estimates with the ith observation removed lies from the vector of model parameter estimates based on all observations. Large values of Cook’s distance indicate that the observation is inluential.

  • Correlation matrix

    A square matrix that contains the correlations among a set of random variables, say, XX X 1 2 k , ,…, . The main diagonal elements of the matrix are unity and the off-diagonal elements rij are the correlations between Xi and Xj .

  • Defect concentration diagram

    A quality tool that graphically shows the location of defects on a part or in a process.

  • Distribution free method(s)

    Any method of inference (hypothesis testing or conidence interval construction) that does not depend on the form of the underlying distribution of the observations. Sometimes called nonparametric method(s).

  • 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.

  • Estimate (or point estimate)

    The numerical value of a point estimator.

  • F-test

    Any test of signiicance involving the F distribution. The most common F-tests 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.

  • Finite population correction factor

    A term in the formula for the variance of a hypergeometric random variable.

  • First-order model

    A model that contains only irstorder terms. For example, the irst-order response surface model in two variables is y xx = + ?? ? ? 0 11 2 2 + + . A irst-order model is also called a main effects model

  • Fraction defective

    In statistical quality control, that portion of a number of units or the output of a process that is defective.

  • Gamma function

    A function used in the probability density function of a gamma random variable that can be considered to extend factorials

  • Hat matrix.

    In multiple regression, the matrix H XXX X = ( ) ? ? -1 . This a projection matrix that maps the vector of observed response values into a vector of itted values by yˆ = = X X X X y Hy ( ) ? ? ?1 .

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