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Textbooks / Statistics / Probability and Statistics for Engineering and the Sciences 8

Probability and Statistics for Engineering and the Sciences 8th Edition - Solutions by Chapter

Probability and Statistics for Engineering and the Sciences | 8th Edition | ISBN: 9780538733526 | Authors: Jay L. Devore

Full solutions for Probability and Statistics for Engineering and the Sciences | 8th Edition

ISBN: 9780538733526

Probability and Statistics for Engineering and the Sciences | 8th Edition | ISBN: 9780538733526 | Authors: Jay L. Devore

Probability and Statistics for Engineering and the Sciences | 8th Edition - Solutions by Chapter

Probability and Statistics for Engineering and the Sciences was written by and is associated to the ISBN: 9780538733526. This textbook survival guide was created for the textbook: Probability and Statistics for Engineering and the Sciences , edition: 8. Since problems from 16 chapters in Probability and Statistics for Engineering and the Sciences have been answered, more than 17639 students have viewed full step-by-step answer. This expansive textbook survival guide covers the following chapters: 16. The full step-by-step solution to problem in Probability and Statistics for Engineering and the Sciences were answered by , our top Statistics solution expert on 08/08/17, 06:52AM.

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.

  • Average run length, or ARL

    The average number of samples taken in a process monitoring or inspection scheme until the scheme signals that the process is operating at a level different from the level in which it began.

  • Backward elimination

    A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

  • Bivariate distribution

    The joint probability distribution of two random variables.

  • Block

    In experimental design, a group of experimental units or material that is relatively homogeneous. The purpose of dividing experimental units into blocks is to produce an experimental design wherein variability within blocks is smaller than variability between blocks. This allows the factors of interest to be compared in an environment that has less variability than in an unblocked experiment.

  • Chance cause

    The portion of the variability in a set of observations that is due to only random forces and which cannot be traced to speciic sources, such as operators, materials, or equipment. Also called a common cause.

  • Coeficient of determination

    See R 2 .

  • 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.

  • 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 random variable.

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

  • Contrast

    A linear function of treatment means with coeficients that total zero. A contrast is a summary of treatment means that is of interest in an 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

  • Eficiency

    A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.

  • Event

    A subset of a sample space.

  • Exponential random variable

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

  • 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.

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