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Solutions for Chapter 5.R: Elementary Statistics: Picturing the World 5th Edition

Elementary Statistics: Picturing the World | 5th Edition | ISBN: 9780321693624 | Authors: Ron Larson

Full solutions for Elementary Statistics: Picturing the World | 5th Edition

ISBN: 9780321693624

Elementary Statistics: Picturing the World | 5th Edition | ISBN: 9780321693624 | Authors: Ron Larson

Solutions for Chapter 5.R

Solutions for Chapter 5.R
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Textbook: Elementary Statistics: Picturing the World
Edition: 5
Author: Ron Larson
ISBN: 9780321693624

This textbook survival guide was created for the textbook: Elementary Statistics: Picturing the World, edition: 5. Chapter 5.R includes 66 full step-by-step solutions. Elementary Statistics: Picturing the World was written by and is associated to the ISBN: 9780321693624. Since 66 problems in chapter 5.R have been answered, more than 10191 students have viewed full step-by-step solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions.

Key Statistics Terms and definitions covered in this textbook
  • 2 k factorial experiment.

    A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

  • Acceptance region

    In hypothesis testing, a region in the sample space of the test statistic such that if the test statistic falls within it, the null hypothesis cannot be rejected. This terminology is used because rejection of H0 is always a strong conclusion and acceptance of H0 is generally a weak conclusion

  • 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.

  • Bimodal distribution.

    A distribution with two modes

  • Central limit theorem

    The simplest form of the central limit theorem states that the sum of n independently distributed random variables will tend to be normally distributed as n becomes large. It is a necessary and suficient condition that none of the variances of the individual random variables are large in comparison to their sum. There are more general forms of the central theorem that allow ininite variances and correlated random variables, and there is a multivariate version of the theorem.

  • 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.

  • Conidence interval

    If it is possible to write a probability statement of the form PL U ( ) ? ? ? ? = ?1 where L and U are functions of only the sample data and ? is a parameter, then the interval between L and U is called a conidence interval (or a 100 1( )% ? ? conidence interval). The interpretation is that a statement that the parameter ? lies in this interval will be true 100 1( )% ? ? of the times that such a statement is made

  • Continuous distribution

    A probability distribution for a continuous random variable.

  • Continuous random variable.

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

  • Control limits

    See Control chart.

  • Correction factor

    A term used for the quantity ( / )( ) 1 1 2 n xi i n ? = that is subtracted from xi i n 2 ? =1 to give the corrected sum of squares deined as (/ ) ( ) 1 1 2 n xx i x i n ? = i ? . The correction factor can also be written as nx 2 .

  • Counting techniques

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

  • Cumulative sum control chart (CUSUM)

    A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t

  • 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.

  • Enumerative study

    A study in which a sample from a population is used to make inference to the population. See Analytic study

  • 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.

  • Exhaustive

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

  • Expected value

    The expected value of a random variable X is its long-term average or mean value. In the continuous case, the expected value of X is E X xf x dx ( ) = ?? ( ) ? ? where f ( ) x is the density function of the random variable X.

  • Finite population correction factor

    A term in the formula for the variance of a hypergeometric random variable.

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