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Textbooks / Statistics / The Practice of Statistics 4

The Practice of Statistics 4th Edition - Solutions by Chapter

The Practice of Statistics | 4th Edition | ISBN: 9781429245593 | Authors: Daren S. Starnes; Dan Yates; David S. Moore

Full solutions for The Practice of Statistics | 4th Edition

ISBN: 9781429245593

The Practice of Statistics | 4th Edition | ISBN: 9781429245593 | Authors: Daren S. Starnes; Dan Yates; David S. Moore

The Practice of Statistics | 4th Edition - Solutions by Chapter

Solutions by Chapter
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Since problems from 12 chapters in The Practice of Statistics have been answered, more than 18422 students have viewed full step-by-step answer. The full step-by-step solution to problem in The Practice of Statistics were answered by , our top Statistics solution expert on 09/04/17, 10:29PM. The Practice of Statistics was written by and is associated to the ISBN: 9781429245593. This textbook survival guide was created for the textbook: The Practice of Statistics, edition: 4. This expansive textbook survival guide covers the following chapters: 12.

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.

  • a-error (or a-risk)

    In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II error).

  • Acceptance region

    In hypothesis testing, a region in the sample space of the test statistic such that if the test statistic falls within it, the null hypothesis cannot be rejected. This terminology is used because rejection of H0 is always a strong conclusion and acceptance of H0 is generally a weak conclusion

  • Additivity property of x 2

    If two independent random variables X1 and X2 are distributed as chi-square with v1 and v2 degrees of freedom, respectively, Y = + X X 1 2 is a chi-square random variable with u = + v v 1 2 degrees of freedom. This generalizes to any number of independent chi-square random variables.

  • 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.

  • Bayes’ theorem

    An equation for a conditional probability such as PA B ( | ) in terms of the reverse conditional probability PB A ( | ).

  • Bivariate normal distribution

    The joint distribution of two normal 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.

  • Center line

    A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.

  • 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.

  • Conidence level

    Another term for the conidence coeficient.

  • Control limits

    See Control chart.

  • 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.

  • Defect concentration diagram

    A quality tool that graphically shows the location of defects on a part or in a process.

  • Degrees of freedom.

    The number of independent comparisons that can be made among the elements of a sample. The term is analogous to the number of degrees of freedom for an object in a dynamic system, which is the number of independent coordinates required to determine the motion of the object.

  • Deming

    W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

  • Design matrix

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

  • 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.

  • Enumerative study

    A study in which a sample from a population is used to make inference to the population. See Analytic study

  • Fixed factor (or fixed effect).

    In analysis of variance, a factor or effect is considered ixed if all the levels of interest for that factor are included in the experiment. Conclusions are then valid about this set of levels only, although when the factor is quantitative, it is customary to it a model to the data for interpolating between these levels.