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Statistics Through Applications 2nd Edition - Solutions by Chapter

Statistics Through Applications | 2nd Edition | ISBN: 9781429219747 | Authors: Daren S. Starnes

Full solutions for Statistics Through Applications | 2nd Edition

ISBN: 9781429219747

Statistics Through Applications | 2nd Edition | ISBN: 9781429219747 | Authors: Daren S. Starnes

Statistics Through Applications | 2nd Edition - Solutions by Chapter

This expansive textbook survival guide covers the following chapters: 10. Since problems from 10 chapters in Statistics Through Applications have been answered, more than 3298 students have viewed full step-by-step answer. The full step-by-step solution to problem in Statistics Through Applications were answered by Sieva Kozinsky, our top Statistics solution expert on 11/10/17, 06:04PM. This textbook survival guide was created for the textbook: Statistics Through Applications, edition: 2. Statistics Through Applications was written by Sieva Kozinsky and is associated to the ISBN: 9781429219747.

Key Statistics Terms and definitions covered in this textbook
  • 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

  • Analysis of variance (ANOVA)

    A method of decomposing the total variability in a set of observations, as measured by the sum of the squares of these observations from their average, into component sums of squares that are associated with speciic deined sources of variation

  • 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

  • Bernoulli trials

    Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

  • Bimodal distribution.

    A distribution with two modes

  • Bivariate distribution

    The joint probability distribution of two random variables.

  • 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).

  • 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.

  • Completely randomized design (or experiment)

    A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order.

  • 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.

  • Convolution

    A method to derive the probability density function of the sum of two independent random variables from an integral (or sum) of probability density (or mass) functions.

  • Cumulative distribution function

    For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.

  • 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.

  • Experiment

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

  • 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.

  • Finite population correction factor

    A term in the formula for the variance of a hypergeometric random variable.

  • 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.

  • Gamma function

    A function used in the probability density function of a gamma random variable that can be considered to extend factorials

  • 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 .

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