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Solutions for Chapter 3.4: Elementary Statistics: A Step By Step Approach 9th Edition

Elementary Statistics: A Step By Step Approach | 9th Edition | ISBN: 9780073534985 | Authors: Allan Bluman

Full solutions for Elementary Statistics: A Step By Step Approach | 9th Edition

ISBN: 9780073534985

Elementary Statistics: A Step By Step Approach | 9th Edition | ISBN: 9780073534985 | Authors: Allan Bluman

Solutions for Chapter 3.4

Solutions for Chapter 3.4
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Textbook: Elementary Statistics: A Step By Step Approach
Edition: 9
Author: Allan Bluman
ISBN: 9780073534985

This expansive textbook survival guide covers the following chapters and their solutions. Since 32 problems in chapter 3.4 have been answered, more than 126685 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: 9780073534985. Chapter 3.4 includes 32 full step-by-step solutions. This textbook survival guide was created for the textbook: Elementary Statistics: A Step By Step Approach , edition: 9.

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

  • a-error (or a-risk)

    In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II error).

  • Attribute control chart

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

  • 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.

  • 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

  • Bivariate normal distribution

    The joint distribution of two normal random variables

  • Box plot (or box and whisker plot)

    A graphical display of data in which the box contains the middle 50% of the data (the interquartile range) with the median dividing it, and the whiskers extend to the smallest and largest values (or some deined lower and upper limits).

  • Conditional probability density function

    The probability density function of the conditional probability distribution of a continuous random variable.

  • Conidence level

    Another term for the conidence coeficient.

  • 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 .

  • Discrete uniform random variable

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

  • Error of estimation

    The difference between an estimated value and the true value.

  • Event

    A subset of a sample space.

  • Exhaustive

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

  • Fixed factor (or fixed effect).

    In analysis of variance, a factor or effect is considered ixed if all the levels of interest for that factor are included in the experiment. Conclusions are then valid about this set of levels only, although when the factor is quantitative, it is customary to it a model to the data for interpolating between these levels.

  • 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.

  • 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.

  • 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

  • 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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