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Solutions for Chapter 9: Analysis of Two-Way Tables

Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card | 8th Edition | ISBN: 9781464158933 | Authors: David S. Moore, George P. McCabe, Bruce A. Craig

Full solutions for Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card | 8th Edition

ISBN: 9781464158933

Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card | 8th Edition | ISBN: 9781464158933 | Authors: David S. Moore, George P. McCabe, Bruce A. Craig

Solutions for Chapter 9: Analysis of Two-Way Tables

Solutions for Chapter 9
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Textbook: Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card
Edition: 8
Author: David S. Moore, George P. McCabe, Bruce A. Craig
ISBN: 9781464158933

This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card, edition: 8. Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card was written by and is associated to the ISBN: 9781464158933. Since 55 problems in chapter 9: Analysis of Two-Way Tables have been answered, more than 33343 students have viewed full step-by-step solutions from this chapter. Chapter 9: Analysis of Two-Way Tables includes 55 full step-by-step solutions.

Key Statistics Terms and definitions covered in this textbook
  • `-error (or `-risk)

    In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).

  • Analytic study

    A study in which a sample from a population is used to make inference to a future population. Stability needs to be assumed. See Enumerative study

  • Axioms of probability

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

  • Categorical data

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

  • Conditional probability

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

  • Conditional probability distribution

    The distribution of a random variable given that the random experiment produces an outcome in an event. The given event might specify values for one or more other random variables

  • Conditional variance.

    The variance of the conditional probability distribution of a random variable.

  • Continuous distribution

    A probability distribution for a continuous random variable.

  • Contour plot

    A two-dimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.

  • Correlation coeficient

    A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).

  • 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 .

  • Cumulative normal distribution function

    The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.

  • Deming

    W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

  • Deming’s 14 points.

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

  • Discrete uniform random variable

    A discrete random variable with a inite range and constant probability mass function.

  • Enumerative study

    A study in which a sample from a population is used to make inference to the population. See Analytic study

  • 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.

  • Expected value

    The expected value of a random variable X is its long-term average or mean value. In the continuous case, the expected value of X is E X xf x dx ( ) = ?? ( ) ? ? where f ( ) x is the density function of the random variable X.

  • False alarm

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

  • 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.

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