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Solutions for Chapter 3.2: Elementary Statistics: Picturing the World 5th Edition

Elementary Statistics: Picturing the World | 5th Edition | ISBN: 9780321693624 | Authors: Ron Larson

Full solutions for Elementary Statistics: Picturing the World | 5th Edition

ISBN: 9780321693624

Elementary Statistics: Picturing the World | 5th Edition | ISBN: 9780321693624 | Authors: Ron Larson

Solutions for Chapter 3.2

Solutions for Chapter 3.2
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Textbook: Elementary Statistics: Picturing the World
Edition: 5
Author: Ron Larson
ISBN: 9780321693624

Chapter 3.2 includes 29 full step-by-step solutions. Elementary Statistics: Picturing the World was written by and is associated to the ISBN: 9780321693624. This textbook survival guide was created for the textbook: Elementary Statistics: Picturing the World, edition: 5. This expansive textbook survival guide covers the following chapters and their solutions. Since 29 problems in chapter 3.2 have been answered, more than 12122 students have viewed full step-by-step solutions from this chapter.

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).

  • Adjusted R 2

    A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

  • All possible (subsets) regressions

    A method of variable selection in regression that examines all possible subsets of the candidate regressor variables. Eficient computer algorithms have been developed for implementing all possible regressions

  • 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.

  • 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.

  • 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

  • Conditional variance.

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

  • Confounding

    When a factorial experiment is run in blocks and the blocks are too small to contain a complete replicate of the experiment, one can run a fraction of the replicate in each block, but this results in losing information on some effects. These effects are linked with or confounded with the blocks. In general, when two factors are varied such that their individual effects cannot be determined separately, their effects are said to be confounded.

  • Conidence level

    Another term for the conidence coeficient.

  • Contingency table.

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

  • Control limits

    See Control chart.

  • Covariance matrix

    A square matrix that contains the variances and covariances among a set of random variables, say, X1 , X X 2 k , , … . The main diagonal elements of the matrix are the variances of the random variables and the off-diagonal elements are the covariances between Xi and Xj . Also called the variance-covariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.

  • 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

  • Deming’s 14 points.

    A management philosophy promoted by W. Edwards Deming that emphasizes the importance of change and quality

  • Density function

    Another name for a probability density function

  • Discrete uniform random variable

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

  • Estimate (or point estimate)

    The numerical value of a point estimator.

  • Generator

    Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.

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