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Solutions for Chapter 8-6: Additional Topics Regarding Hypothesis Testing

Elementary Statistics: A Step by Step Approach 8th ed. | 8th Edition | ISBN: 9780073386102 | Authors: Allan G Bluman Professor Emeritus

Full solutions for Elementary Statistics: A Step by Step Approach 8th ed. | 8th Edition

ISBN: 9780073386102

Elementary Statistics: A Step by Step Approach 8th ed. | 8th Edition | ISBN: 9780073386102 | Authors: Allan G Bluman Professor Emeritus

Solutions for Chapter 8-6: Additional Topics Regarding Hypothesis Testing

Elementary Statistics: A Step by Step Approach 8th ed. was written by and is associated to the ISBN: 9780073386102. Since 9 problems in chapter 8-6: Additional Topics Regarding Hypothesis Testing have been answered, more than 24767 students have viewed full step-by-step solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach 8th ed., edition: 8. Chapter 8-6: Additional Topics Regarding Hypothesis Testing includes 9 full step-by-step solutions.

Key Statistics Terms and definitions covered in this textbook
  • All possible (subsets) regressions

    A method of variable selection in regression that examines all possible subsets of the candidate regressor variables. Eficient computer algorithms have been developed for implementing all possible regressions

  • 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

  • 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.

  • Average run length, or ARL

    The average number of samples taken in a process monitoring or inspection scheme until the scheme signals that the process is operating at a level different from the level in which it began.

  • 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 ( | ).

  • Chi-square test

    Any test of signiicance based on the chi-square distribution. The most common chi-square tests are (1) testing hypotheses about the variance or standard deviation of a normal distribution and (2) testing goodness of it of a theoretical distribution to sample data

  • Continuous random variable.

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

  • Counting techniques

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

  • Cumulative distribution function

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

  • Deining relation

    A subset of effects in a fractional factorial design that deine the aliases in the design.

  • 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.

  • Eficiency

    A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.

  • Erlang random variable

    A continuous random variable that is the sum of a ixed number of independent, exponential random variables.

  • Error propagation

    An analysis of how the variance of the random variable that represents that output of a system depends on the variances of the inputs. A formula exists when the output is a linear function of the inputs and the formula is simpliied if the inputs are assumed to be independent.

  • Exponential random variable

    A series of tests in which changes are made to the system under study

  • Gaussian distribution

    Another name for the normal distribution, based on the strong connection of Karl F. Gauss to the normal distribution; often used in physics and electrical engineering applications

  • 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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