 Chapter 1: Probability Theory
 Chapter 10: Discrete Data Analysis
 Chapter 11: The Analysis of Variance
 Chapter 12: Simple Linear Regression and Correlation
 Chapter 13: Multiple Linear Regression and Nonlinear Regression
 Chapter 14: Multifactor Experimental Design and Analysis
 Chapter 15: Nonparametric Statistical Analysis
 Chapter 16: Quality Control Methods
 Chapter 17: Reliability Analysis and Life Testing
 Chapter 2: Random Variables
 Chapter 3: Discrete Probability Distributions
 Chapter 4: Continuous Probability Distributions
 Chapter 5: The Normal Distribution
 Chapter 6: Descriptive Statistics
 Chapter 7: Statistical Estimation and Sampling Distributions
 Chapter 8: Inferences on a Population Mean
 Chapter 9: Comparing Two Population Means
Probability and Statistics for Engineers and Scientists 4th Edition  Solutions by Chapter
Full solutions for Probability and Statistics for Engineers and Scientists  4th Edition
ISBN: 9781111827045
Probability and Statistics for Engineers and Scientists  4th Edition  Solutions by Chapter
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2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

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.

Bayes’ theorem
An equation for a conditional probability such as PA B (  ) in terms of the reverse conditional probability PB A (  ).

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

Continuous distribution
A probability distribution for a continuous random variable.

Contour plot
A twodimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.

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 offdiagonal elements rij are the correlations between Xi and Xj .

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 offdiagonal elements are the covariances between Xi and Xj . Also called the variancecovariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.

Cumulative distribution function
For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.

Defect
Used in statistical quality control, a defect is a particular type of nonconformance to speciications or requirements. Sometimes defects are classiied into types, such as appearance defects and functional defects.

Defectsperunit control chart
See U chart

Dependent variable
The response variable in regression or a designed 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.

Factorial experiment
A type of experimental design in which every level of one factor is tested in combination with every level of another factor. In general, in a factorial experiment, all possible combinations of factor levels are tested.

Finite population correction factor
A term in the formula for the variance of a hypergeometric random variable.

Fisher’s least signiicant difference (LSD) method
A series of pairwise hypothesis tests of treatment means in an experiment to determine which means differ.

Gamma random variable
A random variable that generalizes an Erlang random variable to noninteger values of the parameter r

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

Generating function
A function that is used to determine properties of the probability distribution of a random variable. See Momentgenerating function

Geometric mean.
The geometric mean of a set of n positive data values is the nth root of the product of the data values; that is, g x i n i n = ( ) = / w 1 1 .