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Solutions for Chapter 2-3: ADDITION RULES

Applied Statistics and Probability for Engineers | 3rd Edition | ISBN: 9780471204541 | Authors: Douglas C. Montgomery, George C. Runger

Full solutions for Applied Statistics and Probability for Engineers | 3rd Edition

ISBN: 9780471204541

Applied Statistics and Probability for Engineers | 3rd Edition | ISBN: 9780471204541 | Authors: Douglas C. Montgomery, George C. Runger

Solutions for Chapter 2-3: ADDITION RULES

Applied Statistics and Probability for Engineers was written by and is associated to the ISBN: 9780471204541. Since 8 problems in chapter 2-3: ADDITION RULES have been answered, more than 22770 students have viewed full step-by-step solutions from this chapter. This textbook survival guide was created for the textbook: Applied Statistics and Probability for Engineers , edition: 3. Chapter 2-3: ADDITION RULES includes 8 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).

  • Average

    See Arithmetic mean.

  • 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.

  • Bivariate distribution

    The joint probability distribution of two random variables.

  • Continuous uniform random variable

    A continuous random variable with range of a inite interval and a constant probability density function.

  • Convolution

    A method to derive the probability density function of the sum of two independent random variables from an integral (or sum) of probability density (or mass) functions.

  • Deining relation

    A subset of effects in a fractional factorial design that deine the aliases in the design.

  • Dependent variable

    The response variable in regression or a designed experiment.

  • Dispersion

    The amount of variability exhibited by data

  • Error of estimation

    The difference between an estimated value and the true value.

  • 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

  • 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 control chart

    See P chart

  • Frequency distribution

    An arrangement of the frequencies of observations in a sample or population according to the values that the observations take on

  • Generating function

    A function that is used to determine properties of the probability distribution of a random variable. See Moment-generating function

  • Generator

    Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.

  • Geometric mean.

    The geometric mean of a set of n positive data values is the nth root of the product of the data values; that is, g x i n i n = ( ) = / w 1 1 .

  • Geometric random variable

    A discrete random variable that is the number of Bernoulli trials until a success occurs.

  • 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 .

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