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Textbooks / Statistics / Probability and Statistics for Engineers and Scientists 4

Probability and Statistics for Engineers and Scientists 4th Edition - Solutions by Chapter

Probability and Statistics for Engineers and Scientists | 4th Edition | ISBN: 9781111827045 | Authors: Anthony J. Hayter

Full solutions for Probability and Statistics for Engineers and Scientists | 4th Edition

ISBN: 9781111827045

Probability and Statistics for Engineers and Scientists | 4th Edition | ISBN: 9781111827045 | Authors: Anthony J. Hayter

Probability and Statistics for Engineers and Scientists | 4th Edition - Solutions by Chapter

Since problems from 17 chapters in Probability and Statistics for Engineers and Scientists have been answered, more than 51485 students have viewed full step-by-step answer. The full step-by-step solution to problem in Probability and Statistics for Engineers and Scientists were answered by , our top Statistics solution expert on 01/12/18, 03:07PM. Probability and Statistics for Engineers and Scientists was written by and is associated to the ISBN: 9781111827045. This expansive textbook survival guide covers the following chapters: 17. This textbook survival guide was created for the textbook: Probability and Statistics for Engineers and Scientists, edition: 4.

Key Statistics Terms and definitions covered in this textbook
  • Additivity property of x 2

    If two independent random variables X1 and X2 are distributed as chi-square with v1 and v2 degrees of freedom, respectively, Y = + X X 1 2 is a chi-square random variable with u = + v v 1 2 degrees of freedom. This generalizes to any number of independent chi-square random variables.

  • 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.

  • Bernoulli trials

    Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

  • Bimodal distribution.

    A distribution with two modes

  • C chart

    An attribute control chart that plots the total number of defects per unit in a subgroup. Similar to a defects-per-unit or U chart.

  • 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.

  • Continuous uniform random variable

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

  • Correlation

    In the most general usage, a measure of the interdependence among data. The concept may include more than two variables. The term is most commonly used in a narrow sense to express the relationship between quantitative variables or ranks.

  • Counting techniques

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

  • Cumulative distribution function

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

  • Defect concentration diagram

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

  • Defects-per-unit control chart

    See U chart

  • Density function

    Another name for a probability density function

  • Erlang random variable

    A continuous random variable that is the sum of a ixed number of independent, exponential random variables.

  • Error of estimation

    The difference between an estimated value and the true value.

  • 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.

  • Gamma random variable

    A random variable that generalizes an Erlang random variable to noninteger values of the parameter r

  • 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