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> > Elementary Statistics: A Step by Step Approach 8th ed. 8

Elementary Statistics: A Step by Step Approach 8th ed. 8th Edition - Solutions by Chapter

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

Elementary Statistics: A Step by Step Approach 8th ed. | 8th Edition - Solutions by Chapter

Solutions by Chapter
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Textbook: Elementary Statistics: A Step by Step Approach 8th ed.
Edition: 8
Author: Allan G Bluman Professor Emeritus
ISBN: 9780073386102

This textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach 8th ed., edition: 8. Elementary Statistics: A Step by Step Approach 8th ed. was written by and is associated to the ISBN: 9780073386102. The full step-by-step solution to problem in Elementary Statistics: A Step by Step Approach 8th ed. were answered by , our top Statistics solution expert on 01/15/18, 03:26PM. This expansive textbook survival guide covers the following chapters: 67. Since problems from 67 chapters in Elementary Statistics: A Step by Step Approach 8th ed. have been answered, more than 16095 students have viewed full step-by-step answer.

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.

  • `-error (or `-risk)

    In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).

  • Adjusted R 2

    A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

  • 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.

  • Bias

    An effect that systematically distorts a statistical result or estimate, preventing it from representing the true quantity of interest.

  • Biased estimator

    Unbiased estimator.

  • 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.

  • Coeficient of determination

    See R 2 .

  • Conidence coeficient

    The probability 1?a associated with a conidence interval expressing the probability that the stated interval will contain the true parameter value.

  • Counting techniques

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

  • Critical region

    In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.

  • Critical value(s)

    The value of a statistic corresponding to a stated signiicance level as determined from the sampling distribution. For example, if PZ z PZ ( )( .) . ? =? = 0 025 . 1 96 0 025, then z0 025 . = 1 9. 6 is the critical value of z at the 0.025 level of signiicance. Crossed factors. Another name for factors that are arranged in a factorial experiment.

  • Crossed factors

    Another name for factors that are arranged in a factorial experiment.

  • Deming’s 14 points.

    A management philosophy promoted by W. Edwards Deming that emphasizes the importance of change and quality

  • Distribution free method(s)

    Any method of inference (hypothesis testing or conidence interval construction) that does not depend on the form of the underlying distribution of the observations. Sometimes called nonparametric method(s).

  • Event

    A subset of a sample space.

  • 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.

  • Experiment

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

  • Frequency distribution

    An arrangement of the frequencies of observations in a sample or population according to the values that the observations take on

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