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Solutions for Chapter 5.3: 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 5.3

Solutions for Chapter 5.3
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Textbook: Elementary Statistics: A Step By Step Approach
Edition: 9
Author: Allan Bluman
ISBN: 9780073534985

Elementary Statistics: A Step By Step Approach was written by and is associated to the ISBN: 9780073534985. 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 , edition: 9. Since 21 problems in chapter 5.3 have been answered, more than 191861 students have viewed full step-by-step solutions from this chapter. Chapter 5.3 includes 21 full step-by-step solutions.

Key Statistics Terms and definitions covered in this textbook
  • 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).

  • 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

  • Asymptotic relative eficiency (ARE)

    Used to compare hypothesis tests. The ARE of one test relative to another is the limiting ratio of the sample sizes necessary to obtain identical error probabilities for the two procedures.

  • Attribute

    A qualitative characteristic of an item or unit, usually arising in quality control. For example, classifying production units as defective or nondefective results in attributes data.

  • Bayes’ estimator

    An estimator for a parameter obtained from a Bayesian method that uses a prior distribution for the parameter along with the conditional distribution of the data given the parameter to obtain the posterior distribution of the parameter. The estimator is obtained from the posterior distribution.

  • Central tendency

    The tendency of data to cluster around some value. Central tendency is usually expressed by a measure of location such as the mean, median, or mode.

  • Chance cause

    The portion of the variability in a set of observations that is due to only random forces and which cannot be traced to speciic sources, such as operators, materials, or equipment. Also called a common cause.

  • Combination.

    A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.

  • Comparative experiment

    An experiment in which the treatments (experimental conditions) that are to be studied are included in the experiment. The data from the experiment are used to evaluate the treatments.

  • Components of variance

    The individual components of the total variance that are attributable to speciic sources. This usually refers to the individual variance components arising from a random or mixed model analysis of variance.

  • Conditional probability

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

  • Control limits

    See Control chart.

  • Defect concentration diagram

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

  • Dispersion

    The amount of variability exhibited by data

  • Estimate (or point estimate)

    The numerical value of a point estimator.

  • Extra sum of squares method

    A method used in regression analysis to conduct a hypothesis test for the additional contribution of one or more variables to a model.

  • First-order model

    A model that contains only irstorder terms. For example, the irst-order response surface model in two variables is y xx = + ?? ? ? 0 11 2 2 + + . A irst-order model is also called a main effects model

  • 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.

  • 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.

  • Geometric mean.

    The geometric mean of a set of n positive data values is the nth root of the product of the data values; that is, g x i n i n = ( ) = / w 1 1 .

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