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Textbooks / Statistics / OpenIntro Statistics, FULL COLOR Hardcover 3

OpenIntro Statistics, FULL COLOR Hardcover 3rd Edition Solutions

Do I need to buy OpenIntro Statistics, FULL COLOR Hardcover | 3rd Edition to pass the class?

ISBN: 9781943450053

OpenIntro Statistics, FULL COLOR Hardcover | 3rd Edition - Solutions by Chapter

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"If I knew then what I knew now I would not have bought the book. It was over priced and My professor only used it a few times."

Textbook: OpenIntro Statistics, FULL COLOR Hardcover
Edition: 3
Author: David M Diez; Christopher D Barr; Mine Çetinkaya-Rundel
ISBN: 9781943450053

The full step-by-step solution to problem in OpenIntro Statistics, FULL COLOR Hardcover were answered by , our top Statistics solution expert on 10/03/18, 06:29PM. Since problems from 0 chapters in OpenIntro Statistics, FULL COLOR Hardcover have been answered, more than 200 students have viewed full step-by-step answer. OpenIntro Statistics, FULL COLOR Hardcover was written by and is associated to the ISBN: 9781943450053. This expansive textbook survival guide covers the following chapters: 0. This textbook survival guide was created for the textbook: OpenIntro Statistics, FULL COLOR Hardcover, edition: 3.

Key Statistics Terms and definitions covered in this textbook
  • Addition rule

    A formula used to determine the probability of the union of two (or more) events from the probabilities of the events and their intersection(s).

  • Asymptotic relative eficiency (ARE)

    Used to compare hypothesis tests. The ARE of one test relative to another is the limiting ratio of the sample sizes necessary to obtain identical error probabilities for the two procedures.

  • Causal variable

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

  • Cause-and-effect diagram

    A chart used to organize the various potential causes of a problem. Also called a ishbone diagram.

  • Conditional probability mass function

    The probability mass function of the conditional probability distribution of a discrete random variable.

  • Conditional variance.

    The variance of the conditional probability distribution of a random variable.

  • Conidence coeficient

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

  • Continuous uniform random variable

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

  • Contour plot

    A two-dimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.

  • Control limits

    See Control chart.

  • Counting techniques

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

  • Crossed factors

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

  • Design matrix

    A matrix that provides the tests that are to be conducted in an experiment.

  • Discrete uniform random variable

    A discrete random variable with a inite range and constant probability mass function.

  • Enumerative study

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

  • Error variance

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

  • Estimate (or point estimate)

    The numerical value of a point estimator.

  • Estimator (or point estimator)

    A procedure for producing an estimate of a parameter of interest. An estimator is usually a function of only sample data values, and when these data values are available, it results in an estimate of the parameter of interest.

  • Exhaustive

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

  • Hat matrix.

    In multiple regression, the matrix H XXX X = ( ) ? ? -1 . This a projection matrix that maps the vector of observed response values into a vector of itted values by yˆ = = X X X X y Hy ( ) ? ? ?1 .