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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 Sieva Kozinsky 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 5410 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 Sieva Kozinsky, our top Statistics solution expert on 08/08/17, 06:52AM.

Key Statistics Terms and definitions covered in this textbook
  • 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 normal distribution

    The joint distribution of two normal random variables

  • 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.

  • Conditional probability

    The probability of an event given that the random experiment produces an outcome in another event.

  • Confounding

    When a factorial experiment is run in blocks and the blocks are too small to contain a complete replicate of the experiment, one can run a fraction of the replicate in each block, but this results in losing information on some effects. These effects are linked with or confounded with the blocks. In general, when two factors are varied such that their individual effects cannot be determined separately, their effects are said to be confounded.

  • Contingency table.

    A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria

  • Continuous distribution

    A probability distribution for a continuous random variable.

  • 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 .

  • Correlation

    In the most general usage, a measure of the interdependence among data. The concept may include more than two variables. The term is most commonly used in a narrow sense to express the relationship between quantitative variables or ranks.

  • 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).

  • Defects-per-unit control chart

    See U chart

  • Design matrix

    A matrix that provides the tests that are to be conducted in an experiment.

  • Discrete random variable

    A random variable with a inite (or countably ininite) range.

  • Error of estimation

    The difference between an estimated value and the true value.

  • Error variance

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

  • Event

    A subset of a sample space.

  • False alarm

    A signal from a control chart when no assignable causes are present

  • Fisher’s least signiicant difference (LSD) method

    A series of pair-wise hypothesis tests of treatment means in an experiment to determine which means differ.

  • 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.

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