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The Practice of Statistics 5th Edition - Solutions by Chapter

Full solutions for The Practice of Statistics | 5th Edition

ISBN: 9781464108730

The Practice of Statistics | 5th Edition - Solutions by Chapter

Solutions by Chapter
4 5 0 362 Reviews
Textbook: The Practice of Statistics
Edition: 5
Author: Daren S. Starnes, Josh Tabor
ISBN: 9781464108730

The full step-by-step solution to problem in The Practice of Statistics were answered by , our top Statistics solution expert on 03/19/18, 03:52PM. This expansive textbook survival guide covers the following chapters: 44. Since problems from 44 chapters in The Practice of Statistics have been answered, more than 11113 students have viewed full step-by-step answer. This textbook survival guide was created for the textbook: The Practice of Statistics, edition: 5. The Practice of Statistics was written by and is associated to the ISBN: 9781464108730.

Key Statistics Terms and definitions covered in this textbook
  • Analytic study

    A study in which a sample from a population is used to make inference to a future population. Stability needs to be assumed. See Enumerative study

  • Assignable cause

    The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.

  • Bernoulli trials

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

  • Categorical data

    Data consisting of counts or observations that can be classiied into categories. The categories may be descriptive.

  • Causal variable

    When y fx = ( ) and y is considered to be caused by x, x is sometimes called a causal variable

  • 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.

  • Chi-square test

    Any test of signiicance based on the chi-square distribution. The most common chi-square tests are (1) testing hypotheses about the variance or standard deviation of a normal distribution and (2) testing goodness of it of a theoretical distribution to sample data

  • 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 density function

    The probability density function of the conditional probability distribution of a continuous random variable.

  • Conditional probability distribution

    The distribution of a random variable given that the random experiment produces an outcome in an event. The given event might specify values for one or more other random variables

  • 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.

  • Covariance

    A measure of association between two random variables obtained as the expected value of the product of the two random variables around their means; that is, Cov(X Y, ) [( )( )] =? ? E X Y ? ? X Y .

  • Discrete random variable

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

  • Dispersion

    The amount of variability exhibited by data

  • Distribution function

    Another name for a cumulative distribution function.

  • Error variance

    The variance of an error term or component in a model.

  • F distribution.

    The distribution of the random variable deined as the ratio of two independent chi-square random variables, each divided by its number of degrees of freedom.

  • 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.

  • Fraction defective control chart

    See P chart

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