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Textbooks / Statistics / Mathematical Statistics and Data Analysis 3

Mathematical Statistics and Data Analysis 3rd Edition - Solutions by Chapter

Mathematical Statistics and Data Analysis | 3rd Edition | ISBN: 9788131519547 | Authors: John A. Rice

Full solutions for Mathematical Statistics and Data Analysis | 3rd Edition

ISBN: 9788131519547

Mathematical Statistics and Data Analysis | 3rd Edition | ISBN: 9788131519547 | Authors: John A. Rice

Mathematical Statistics and Data Analysis | 3rd Edition - Solutions by Chapter

This expansive textbook survival guide covers the following chapters: 14. This textbook survival guide was created for the textbook: Mathematical Statistics and Data Analysis, edition: 3. The full step-by-step solution to problem in Mathematical Statistics and Data Analysis were answered by , our top Statistics solution expert on 01/05/18, 06:27PM. Mathematical Statistics and Data Analysis was written by and is associated to the ISBN: 9788131519547. Since problems from 14 chapters in Mathematical Statistics and Data Analysis have been answered, more than 12933 students have viewed full step-by-step answer.

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.

  • Box plot (or box and whisker plot)

    A graphical display of data in which the box contains the middle 50% of the data (the interquartile range) with the median dividing it, and the whiskers extend to the smallest and largest values (or some deined lower and upper limits).

  • 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.

  • Central composite design (CCD)

    A second-order response surface design in k variables consisting of a two-level factorial, 2k axial runs, and one or more center points. The two-level factorial portion of a CCD can be a fractional factorial design when k is large. The CCD is the most widely used design for itting a second-order model.

  • 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.

  • 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.

  • 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.

  • Continuous random variable.

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

  • Continuous uniform random variable

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

  • 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.

  • 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 of estimation

    The difference between an estimated value and the true value.

  • 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.

  • F-test

    Any test of signiicance involving the F distribution. The most common F-tests are (1) testing hypotheses about the variances or standard deviations of two independent normal distributions, (2) testing hypotheses about treatment means or variance components in the analysis of variance, and (3) testing signiicance of regression or tests on subsets of parameters in a regression model.

  • Factorial experiment

    A type of experimental design in which every level of one factor is tested in combination with every level of another factor. In general, in a factorial experiment, all possible combinations of factor levels are tested.

  • False alarm

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

  • Fractional factorial experiment

    A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.

  • Geometric mean.

    The geometric mean of a set of n positive data values is the nth root of the product of the data values; that is, g x i n i n = ( ) = / w 1 1 .

  • Geometric random variable

    A discrete random variable that is the number of Bernoulli trials until a success occurs.

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