Solutions for Chapter 6.3: Binomial and Geometric Random Variables

Full solutions for The Practice of Statistics | 5th Edition

ISBN: 9781464108730

Solutions for Chapter 6.3: Binomial and Geometric Random Variables

Solutions for Chapter 6.3
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Textbook: The Practice of Statistics
Edition: 5
Author: Daren S. Starnes, Josh Tabor
ISBN: 9781464108730

This textbook survival guide was created for the textbook: The Practice of Statistics, edition: 5. Chapter 6.3: Binomial and Geometric Random Variables includes 39 full step-by-step solutions. This expansive textbook survival guide covers the following chapters and their solutions. Since 39 problems in chapter 6.3: Binomial and Geometric Random Variables have been answered, more than 8954 students have viewed full step-by-step solutions from this chapter. The Practice of Statistics was written by and is associated to the ISBN: 9781464108730.

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).

  • 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.

  • Biased estimator

    Unbiased estimator.

  • Center line

    A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.

  • 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.

  • Completely randomized design (or experiment)

    A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order.

  • 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 uniform random variable

    A continuous random variable with range of a inite interval and a constant probability density function.

  • Cumulative distribution function

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

  • Curvilinear regression

    An expression sometimes used for nonlinear regression models or polynomial regression models.

  • Deining relation

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

  • Discrete random variable

    A random variable with a inite (or countably ininite) range.

  • Dispersion

    The amount of variability exhibited by data

  • 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.

  • 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.

  • Fraction defective control chart

    See P chart

  • Gamma function

    A function used in the probability density function of a gamma random variable that can be considered to extend factorials

  • Generator

    Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.

  • Harmonic mean

    The harmonic mean of a set of data values is the reciprocal of the arithmetic mean of the reciprocals of the data values; that is, h n x i n i = ? ? ? ? ? = ? ? 1 1 1 1 g .

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