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Solutions for Chapter 2: Stats: Data and Models 4th Edition

Stats: Data and Models | 4th Edition | ISBN: 9780321986498 | Authors: Richard D. De Veaux, Paul F. Velleman, David E. Bock

Full solutions for Stats: Data and Models | 4th Edition

ISBN: 9780321986498

Stats: Data and Models | 4th Edition | ISBN: 9780321986498 | Authors: Richard D. De Veaux, Paul F. Velleman, David E. Bock

Solutions for Chapter 2

Solutions for Chapter 2
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Textbook: Stats: Data and Models
Edition: 4
Author: Richard D. De Veaux, Paul F. Velleman, David E. Bock
ISBN: 9780321986498

Since 35 problems in chapter 2 have been answered, more than 37536 students have viewed full step-by-step solutions from this chapter. Chapter 2 includes 35 full step-by-step solutions. Stats: Data and Models was written by and is associated to the ISBN: 9780321986498. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Stats: Data and Models , edition: 4.

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

  • 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).

  • Attribute control chart

    Any control chart for a discrete random variable. See Variables control chart.

  • Axioms of probability

    A set of rules that probabilities deined on a sample space must follow. See Probability

  • 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

  • Bayes’ theorem

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

  • 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).

  • Categorical data

    Data consisting of counts or observations that can be classiied into categories. The categories may be descriptive.

  • Chi-square (or chi-squared) random variable

    A continuous random variable that results from the sum of squares of independent standard normal random variables. It is a special case of a gamma random variable.

  • Correlation matrix

    A square matrix that contains the correlations among a set of random variables, say, XX X 1 2 k , ,…, . The main diagonal elements of the matrix are unity and the off-diagonal elements rij are the correlations between Xi and Xj .

  • 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.

  • Cumulative distribution function

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

  • Distribution function

    Another name for a cumulative distribution function.

  • Estimate (or point estimate)

    The numerical value of a point estimator.

  • Event

    A subset of a sample space.

  • 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.

  • 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.

  • 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.

  • Gamma random variable

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

  • 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 .

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