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Solutions for Chapter 2: Displaying and Describing Categorical Data

Stats Modeling the World | 4th Edition | ISBN: 9780321854018 | Authors: David E. Bock, Paul F. Velleman, Richard D. De Veaux

Full solutions for Stats Modeling the World | 4th Edition

ISBN: 9780321854018

Stats Modeling the World | 4th Edition | ISBN: 9780321854018 | Authors: David E. Bock, Paul F. Velleman, Richard D. De Veaux

Solutions for Chapter 2: Displaying and Describing Categorical Data

Solutions for Chapter 2
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Textbook: Stats Modeling the World
Edition: 4
Author: David E. Bock, Paul F. Velleman, Richard D. De Veaux
ISBN: 9780321854018

This textbook survival guide was created for the textbook: Stats Modeling the World, edition: 4. Since 42 problems in chapter 2: Displaying and Describing Categorical Data have been answered, more than 21389 students have viewed full step-by-step solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 2: Displaying and Describing Categorical Data includes 42 full step-by-step solutions. Stats Modeling the World was written by and is associated to the ISBN: 9780321854018.

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).

  • Analysis of variance (ANOVA)

    A method of decomposing the total variability in a set of observations, as measured by the sum of the squares of these observations from their average, into component sums of squares that are associated with speciic deined sources of variation

  • 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.

  • 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.

  • Backward elimination

    A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

  • 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.

  • 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.

  • Contingency table.

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

  • Contrast

    A linear function of treatment means with coeficients that total zero. A contrast is a summary of treatment means that is of interest in an experiment.

  • 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.

  • Correlation coeficient

    A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).

  • Counting techniques

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

  • Cumulative sum control chart (CUSUM)

    A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t

  • Defect concentration diagram

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

  • Density function

    Another name for a probability density function

  • Dependent variable

    The response variable in regression or a designed experiment.

  • Designed experiment

    An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

  • Distribution free method(s)

    Any method of inference (hypothesis testing or conidence interval construction) that does not depend on the form of the underlying distribution of the observations. Sometimes called nonparametric method(s).

  • Enumerative study

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

  • 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

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