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Solutions for Chapter 10: Re-expressing Data: Get It Straight!

Stats: Modeling The World | 3rd Edition | ISBN: 9780131359581 | Authors: David E. Bock

Full solutions for Stats: Modeling The World | 3rd Edition

ISBN: 9780131359581

Stats: Modeling The World | 3rd Edition | ISBN: 9780131359581 | Authors: David E. Bock

Solutions for Chapter 10: Re-expressing Data: Get It Straight!

Solutions for Chapter 10
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Textbook: Stats: Modeling The World
Edition: 3
Author: David E. Bock
ISBN: 9780131359581

Stats: Modeling The World was written by and is associated to the ISBN: 9780131359581. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Stats: Modeling The World , edition: 3. Since 30 problems in chapter 10: Re-expressing Data: Get It Straight! have been answered, more than 45068 students have viewed full step-by-step solutions from this chapter. Chapter 10: Re-expressing Data: Get It Straight! includes 30 full step-by-step solutions.

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

  • Arithmetic mean

    The arithmetic mean of a set of numbers x1 , x2 ,…, xn is their sum divided by the number of observations, or ( / )1 1 n xi t n ? = . The arithmetic mean is usually denoted by x , and is often called the average

  • 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.

  • Attribute control chart

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

  • Bimodal distribution.

    A distribution with two modes

  • Bivariate normal distribution

    The joint distribution of two normal random variables

  • Coeficient of determination

    See R 2 .

  • Combination.

    A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.

  • 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.

  • Contingency table.

    A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria

  • Continuous uniform random variable

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

  • 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 .

  • Counting techniques

    Formulas used to determine the number of elements in sample spaces and events.

  • 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.

  • Error of estimation

    The difference between an estimated value and the true value.

  • Estimate (or point estimate)

    The numerical value of a point estimator.

  • Finite population correction factor

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

  • Fraction defective control chart

    See P chart

  • 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 .