Solutions for Chapter 12: Nonparametric Hypothesis Tests

Introduction to Probability and Statistics for Engineers and Scientists | 5th Edition | ISBN: 9780123948113 | Authors: Sheldon M. Ross

Full solutions for Introduction to Probability and Statistics for Engineers and Scientists | 5th Edition

ISBN: 9780123948113

Introduction to Probability and Statistics for Engineers and Scientists | 5th Edition | ISBN: 9780123948113 | Authors: Sheldon M. Ross

Solutions for Chapter 12: Nonparametric Hypothesis Tests

Solutions for Chapter 12
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Textbook: Introduction to Probability and Statistics for Engineers and Scientists
Edition: 5
Author: Sheldon M. Ross
ISBN: 9780123948113

Since 22 problems in chapter 12: Nonparametric Hypothesis Tests have been answered, more than 3058 students have viewed full step-by-step solutions from this chapter. Chapter 12: Nonparametric Hypothesis Tests includes 22 full step-by-step solutions. Introduction to Probability and Statistics for Engineers and Scientists was written by Patricia and is associated to the ISBN: 9780123948113. This textbook survival guide was created for the textbook: Introduction to Probability and Statistics for Engineers and Scientists, edition: 5. This expansive textbook survival guide covers the following chapters and their 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

  • Additivity property of x 2

    If two independent random variables X1 and X2 are distributed as chi-square with v1 and v2 degrees of freedom, respectively, Y = + X X 1 2 is a chi-square random variable with u = + v v 1 2 degrees of freedom. This generalizes to any number of independent chi-square random variables.

  • 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.

  • Axioms of probability

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

  • Bimodal distribution.

    A distribution with two modes

  • Bivariate distribution

    The joint probability distribution of two random variables.

  • Conditional variance.

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

  • Continuous random variable.

    A random variable with an interval (either inite or ininite) of real numbers for its range.

  • Cumulative distribution function

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

  • Curvilinear regression

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

  • Defect concentration diagram

    A quality tool that graphically shows the location of defects on a part or in a process.

  • Design matrix

    A matrix that provides the tests that are to be conducted in an experiment.

  • Discrete uniform random variable

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

  • Distribution function

    Another name for a cumulative distribution function.

  • Error of estimation

    The difference between an estimated value and the true value.

  • Exhaustive

    A property of a collection of events that indicates that their union equals the 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.

  • 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.

  • 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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