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Solutions for Chapter 16-12: IMPLEMENTING SPC

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 16-12: IMPLEMENTING SPC

Solutions for Chapter 16-12
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Textbook: Applied Statistics and Probability for Engineers
Edition: 3
Author: Douglas C. Montgomery, George C. Runger
ISBN: 9780471204541

Chapter 16-12: IMPLEMENTING SPC includes 29 full step-by-step solutions. Applied Statistics and Probability for Engineers was written by and is associated to the ISBN: 9780471204541. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Applied Statistics and Probability for Engineers , edition: 3. Since 29 problems in chapter 16-12: IMPLEMENTING SPC have been answered, more than 18162 students have viewed full step-by-step solutions from this chapter.

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).

  • Attribute control chart

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

  • Bivariate distribution

    The joint probability distribution of two random variables.

  • 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

  • Comparative experiment

    An experiment in which the treatments (experimental conditions) that are to be studied are included in the experiment. The data from the experiment are used to evaluate the treatments.

  • Conditional probability distribution

    The distribution of a random variable given that the random experiment produces an outcome in an event. The given event might specify values for one or more other random variables

  • 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

  • Consistent estimator

    An estimator that converges in probability to the true value of the estimated parameter as the sample size increases.

  • Continuous uniform random variable

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

  • Correlation coeficient

    A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).

  • Crossed factors

    Another name for factors that are arranged in a factorial experiment.

  • Decision interval

    A parameter in a tabular CUSUM algorithm that is determined from a trade-off between false alarms and the detection of assignable causes.

  • Designed experiment

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

  • Discrete distribution

    A probability distribution for a discrete random variable

  • Error mean square

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

  • Estimator (or point estimator)

    A procedure for producing an estimate of a parameter of interest. An estimator is usually a function of only sample data values, and when these data values are available, it results in an estimate of the parameter of interest.

  • Event

    A subset of a sample space.

  • Fraction defective control chart

    See P chart

  • 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.

  • 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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