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# Solutions for Chapter 5.3: Applied Statistics and Probability for Engineers 6th Edition

## Full solutions for Applied Statistics and Probability for Engineers | 6th Edition

ISBN: 9781118539712

Solutions for Chapter 5.3

Solutions for Chapter 5.3
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##### ISBN: 9781118539712

This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Applied Statistics and Probability for Engineers , edition: 6. Chapter 5.3 includes 14 full step-by-step solutions. Applied Statistics and Probability for Engineers was written by and is associated to the ISBN: 9781118539712. Since 14 problems in chapter 5.3 have been answered, more than 281091 students have viewed full step-by-step solutions from this chapter.

Key Statistics Terms and definitions covered in this textbook
• 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).

• 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

• Bernoulli trials

Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

• Chance cause

The portion of the variability in a set of observations that is due to only random forces and which cannot be traced to speciic sources, such as operators, materials, or equipment. Also called a common cause.

• Coeficient of determination

See R 2 .

• 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.

• Conditional probability mass function

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

• Defects-per-unit control chart

See U chart

• Deming

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

• Discrete uniform random variable

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

• 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).

• 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 of estimation

The difference between an estimated value and the true value.

• Error sum of squares

In analysis of variance, this is the portion of total variability that is due to the random component in the data. It is usually based on replication of observations at certain treatment combinations in the experiment. It is sometimes called the residual sum of squares, although this is really a better term to use only when the sum of squares is based on the remnants of a model-itting process and not on replication.

• Error variance

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

• Exhaustive

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

• F-test

Any test of signiicance involving the F distribution. The most common F-tests are (1) testing hypotheses about the variances or standard deviations of two independent normal distributions, (2) testing hypotheses about treatment means or variance components in the analysis of variance, and (3) testing signiicance of regression or tests on subsets of parameters in a regression model.

• Fraction defective

In statistical quality control, that portion of a number of units or the output of a process that is defective.

• 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.