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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 44630 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.

  • 2 k p - factorial experiment

    A fractional factorial experiment with k factors tested in a 2 ? p fraction with all factors tested at only two levels (settings) each

  • Adjusted R 2

    A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

  • Asymptotic relative eficiency (ARE)

    Used to compare hypothesis tests. The ARE of one test relative to another is the limiting ratio of the sample sizes necessary to obtain identical error probabilities for the two procedures.

  • Bivariate distribution

    The joint probability distribution of two random variables.

  • Central tendency

    The tendency of data to cluster around some value. Central tendency is usually expressed by a measure of location such as the mean, median, or mode.

  • 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.

  • 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

  • Conidence coeficient

    The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.

  • Conidence level

    Another term for the conidence coeficient.

  • Continuous random variable.

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

  • Contour plot

    A two-dimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.

  • Density function

    Another name for a probability density function

  • Designed experiment

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

  • Erlang random variable

    A continuous random variable that is the sum of a ixed number of independent, exponential random variables.

  • Error mean square

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

  • Error variance

    The variance of an error term or component in a model.

  • Forward selection

    A method of variable selection in regression, where variables are inserted one at a time into the model until no other variables that contribute signiicantly to the model can be found.

  • 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.

  • 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 .