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Solutions for Chapter 3-5: DISCRETE UNIFORM DISTRIBUTION

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 3-5: DISCRETE UNIFORM DISTRIBUTION

Since 9 problems in chapter 3-5: DISCRETE UNIFORM DISTRIBUTION have been answered, more than 21237 students have viewed full step-by-step solutions from this chapter. Chapter 3-5: DISCRETE UNIFORM DISTRIBUTION includes 9 full step-by-step solutions. This textbook survival guide was created for the textbook: Applied Statistics and Probability for Engineers , edition: 3. This expansive textbook survival guide covers the following chapters and their solutions. Applied Statistics and Probability for Engineers was written by and is associated to the ISBN: 9780471204541.

Key Statistics Terms and definitions covered in this textbook
  • 2 k factorial experiment.

    A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

  • Addition rule

    A formula used to determine the probability of the union of two (or more) events from the probabilities of the events and their intersection(s).

  • Alias

    In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

  • Chi-square test

    Any test of signiicance based on the chi-square distribution. The most common chi-square 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

  • Coeficient of determination

    See R 2 .

  • 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.

  • Continuous uniform random variable

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

  • Correction factor

    A term used for the quantity ( / )( ) 1 1 2 n xi i n ? = that is subtracted from xi i n 2 ? =1 to give the corrected sum of squares deined as (/ ) ( ) 1 1 2 n xx i x i n ? = i ? . The correction factor can also be written as nx 2 .

  • Covariance matrix

    A square matrix that contains the variances and covariances among a set of random variables, say, X1 , X X 2 k , , … . The main diagonal elements of the matrix are the variances of the random variables and the off-diagonal elements are the covariances between Xi and Xj . Also called the variance-covariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.

  • Cumulative distribution function

    For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.

  • Defect

    Used in statistical quality control, a defect is a particular type of nonconformance to speciications or requirements. Sometimes defects are classiied into types, such as appearance defects and functional defects.

  • Defects-per-unit control chart

    See U chart

  • Dependent variable

    The response variable in regression or a designed experiment.

  • Designed experiment

    An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

  • Error mean square

    The error sum of squares divided by its number of degrees of freedom.

  • Error of estimation

    The difference between an estimated value and the true value.

  • Exponential random variable

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

  • Factorial experiment

    A type of experimental design in which every level of one factor is tested in combination with every level of another factor. In general, in a factorial experiment, all possible combinations of factor levels are tested.

  • Gamma function

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

  • Gaussian distribution

    Another name for the normal distribution, based on the strong connection of Karl F. Gauss to the normal distribution; often used in physics and electrical engineering applications

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