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Textbooks / Statistics / Elementary Statistics: A Step by Step Approach 8th ed. 8

# Elementary Statistics: A Step by Step Approach 8th ed. 8th Edition - Solutions by Chapter ## Full solutions for Elementary Statistics: A Step by Step Approach 8th ed. | 8th Edition

ISBN: 9780073386102 Elementary Statistics: A Step by Step Approach 8th ed. | 8th Edition - Solutions by Chapter

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##### ISBN: 9780073386102

This textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach 8th ed., edition: 8. Elementary Statistics: A Step by Step Approach 8th ed. was written by and is associated to the ISBN: 9780073386102. The full step-by-step solution to problem in Elementary Statistics: A Step by Step Approach 8th ed. were answered by , our top Statistics solution expert on 01/15/18, 03:26PM. This expansive textbook survival guide covers the following chapters: 67. Since problems from 67 chapters in Elementary Statistics: A Step by Step Approach 8th ed. have been answered, more than 24606 students have viewed full step-by-step answer.

Key Statistics Terms and definitions covered in this textbook
• Additivity property of x 2

If two independent random variables X1 and X2 are distributed as chi-square with v1 and v2 degrees of freedom, respectively, Y = + X X 1 2 is a chi-square random variable with u = + v v 1 2 degrees of freedom. This generalizes to any number of independent chi-square random variables.

• 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.

• Biased estimator

Unbiased estimator.

• Categorical data

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

• Conditional probability mass function

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

• 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.

• 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.

• Curvilinear regression

An expression sometimes used for nonlinear regression models or polynomial regression models.

• Defect concentration diagram

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

• Deming

W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

• Deming’s 14 points.

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

• Design matrix

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

• Eficiency

A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.

• Empirical model

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

• Error propagation

An analysis of how the variance of the random variable that represents that output of a system depends on the variances of the inputs. A formula exists when the output is a linear function of the inputs and the formula is simpliied if the inputs are assumed to be independent.

• 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.

• Fractional factorial experiment

A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.

• 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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