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Solutions for Chapter 8-1: Hypothesis Testing

Elementary Statistics: A Step by Step Approach | 7th Edition | ISBN: 9780073534978 | Authors: Allan G. Bluman

Full solutions for Elementary Statistics: A Step by Step Approach | 7th Edition

ISBN: 9780073534978

Elementary Statistics: A Step by Step Approach | 7th Edition | ISBN: 9780073534978 | Authors: Allan G. Bluman

Solutions for Chapter 8-1: Hypothesis Testing

This textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach, edition: 7. This expansive textbook survival guide covers the following chapters and their solutions. Since 13 problems in chapter 8-1: Hypothesis Testing have been answered, more than 26396 students have viewed full step-by-step solutions from this chapter. Elementary Statistics: A Step by Step Approach was written by and is associated to the ISBN: 9780073534978. Chapter 8-1: Hypothesis Testing includes 13 full step-by-step solutions.

Key Statistics Terms and definitions covered in this textbook
  • Biased estimator

    Unbiased estimator.

  • Bivariate normal distribution

    The joint distribution of two normal random variables

  • Coeficient of determination

    See R 2 .

  • Conditional probability mass function

    The probability mass function of the conditional probability distribution of a discrete random variable.

  • Continuity correction.

    A correction factor used to improve the approximation to binomial probabilities from a normal distribution.

  • Continuous random variable.

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

  • Continuous uniform random variable

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

  • Convolution

    A method to derive the probability density function of the sum of two independent random variables from an integral (or sum) of probability density (or mass) functions.

  • Defects-per-unit control chart

    See U chart

  • Degrees of freedom.

    The number of independent comparisons that can be made among the elements of a sample. The term is analogous to the number of degrees of freedom for an object in a dynamic system, which is the number of independent coordinates required to determine the motion of the object.

  • Design matrix

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

  • Discrete distribution

    A probability distribution for a discrete random variable

  • Distribution function

    Another name for a cumulative distribution function.

  • F distribution.

    The distribution of the random variable deined as the ratio of two independent chi-square random variables, each divided by its number of degrees of freedom.

  • 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.

  • 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.

  • Fraction defective control chart

    See P chart

  • 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.

  • Geometric random variable

    A discrete random variable that is the number of Bernoulli trials until a success occurs.

  • 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 .

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