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Textbooks / Statistics / Statistics for Business and Economics 13

Statistics for Business and Economics 13th Edition Solutions

Do I need to buy Statistics for Business and Economics | 13th Edition to pass the class?

ISBN: 9780134506593

Statistics for Business and Economics | 13th Edition - Solutions by Chapter

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Textbook: Statistics for Business and Economics
Edition: 13
Author: James T. McClave; P. George Benson; Terry Sincich
ISBN: 9780134506593

Statistics for Business and Economics was written by and is associated to the ISBN: 9780134506593. This textbook survival guide was created for the textbook: Statistics for Business and Economics, edition: 13. This expansive textbook survival guide covers the following chapters: 0. Since problems from 0 chapters in Statistics for Business and Economics have been answered, more than 200 students have viewed full step-by-step answer. The full step-by-step solution to problem in Statistics for Business and Economics were answered by , our top Statistics solution expert on 09/27/18, 09:50PM.

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).

  • 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.

  • Binomial random variable

    A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.

  • Cause-and-effect diagram

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

  • Central limit theorem

    The simplest form of the central limit theorem states that the sum of n independently distributed random variables will tend to be normally distributed as n becomes large. It is a necessary and suficient condition that none of the variances of the individual random variables are large in comparison to their sum. There are more general forms of the central theorem that allow ininite variances and correlated random variables, and there is a multivariate version of the theorem.

  • Comparative experiment

    An experiment in which the treatments (experimental conditions) that are to be studied are included in the experiment. The data from the experiment are used to evaluate the treatments.

  • Contingency table.

    A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria

  • Continuous distribution

    A probability distribution for a continuous random variable.

  • 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 chart

    A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the in-control value of the parameter that is being monitored and lower and upper control limits. The control limits are determined by statistical criteria and are not arbitrary, nor are they related to speciication limits. If sample points fall within the control limits, the process is said to be in-control, or free from assignable causes. Points beyond the control limits indicate an out-of-control process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.

  • Control limits

    See Control chart.

  • Correlation matrix

    A square matrix that contains the correlations among a set of random variables, say, XX X 1 2 k , ,…, . The main diagonal elements of the matrix are unity and the off-diagonal elements rij are the correlations between Xi and Xj .

  • Counting techniques

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

  • Degrees of freedom.

    The number of independent comparisons that can be made among the elements of a sample. The term is analogous to the number of degrees of freedom for an object in a dynamic system, which is the number of independent coordinates required to determine the motion of the object.

  • Dependent variable

    The response variable in regression or a designed experiment.

  • Empirical model

    A model to relate a response to one or more regressors or factors that is developed from data obtained from the system.

  • 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.

  • Generating function

    A function that is used to determine properties of the probability distribution of a random variable. See Moment-generating function