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Textbooks / Statistics / Contemporary Mathematics 6

Contemporary Mathematics 6th Edition - Solutions by Chapter

Contemporary Mathematics | 6th Edition | ISBN: 9780538481267 | Authors: Robert Brechner

Full solutions for Contemporary Mathematics | 6th Edition

ISBN: 9780538481267

Contemporary Mathematics | 6th Edition | ISBN: 9780538481267 | Authors: Robert Brechner

Contemporary Mathematics | 6th Edition - Solutions by Chapter

The full step-by-step solution to problem in Contemporary Mathematics were answered by , our top Statistics solution expert on 03/13/18, 06:38PM. This textbook survival guide was created for the textbook: Contemporary Mathematics, edition: 6. This expansive textbook survival guide covers the following chapters: 25. Contemporary Mathematics was written by and is associated to the ISBN: 9780538481267. Since problems from 25 chapters in Contemporary Mathematics have been answered, more than 5377 students have viewed full step-by-step answer.

Key Statistics Terms and definitions covered in this textbook
  • Assignable cause

    The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.

  • Bivariate distribution

    The joint probability distribution of two random variables.

  • 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

  • Conditional probability

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

  • Covariance

    A measure of association between two random variables obtained as the expected value of the product of the two random variables around their means; that is, Cov(X Y, ) [( )( )] =? ? E X Y ? ? X Y .

  • Critical value(s)

    The value of a statistic corresponding to a stated signiicance level as determined from the sampling distribution. For example, if PZ z PZ ( )( .) . ? =? = 0 025 . 1 96 0 025, then z0 025 . = 1 9. 6 is the critical value of z at the 0.025 level of signiicance. Crossed factors. Another name for factors that are arranged in a factorial experiment.

  • Curvilinear regression

    An expression sometimes used for nonlinear regression models or polynomial regression models.

  • Deming’s 14 points.

    A management philosophy promoted by W. Edwards Deming that emphasizes the importance of change and quality

  • Dependent variable

    The response variable in regression or a designed experiment.

  • Distribution free method(s)

    Any method of inference (hypothesis testing or conidence interval construction) that does not depend on the form of the underlying distribution of the observations. Sometimes called nonparametric method(s).

  • Empirical model

    A model to relate a response to one or more regressors or factors that is developed from data obtained from the system.

  • Error variance

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

  • Extra sum of squares method

    A method used in regression analysis to conduct a hypothesis test for the additional contribution of one or more variables to a model.

  • 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.

  • 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.

  • 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.

  • 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

  • Gamma random variable

    A random variable that generalizes an Erlang random variable to noninteger values of the parameter r

  • Generating function

    A function that is used to determine properties of the probability distribution of a random variable. See Moment-generating function

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