 13.4.51E: An experiment was conducted to investigate leaking current in a SOS...
 13.4.52SE: Consider the following computer output. (a) How many levels of the ...
 13.4.53SE: Consider the following computer output. (a) How many levels of the ...
 13.4.54SE: An article in Lubrication Engineering (December 1990) described the...
 13.4.55SE: An article in the IEEE Transactions on Components, Hybrids, and Man...
 13.4.56SE: An article in the Journal of Quality Technology [(1982, Vol. 14(2),...
 13.4.57SE: An article in the Journal of Agricultural Engineering Research (199...
 13.4.58SE: An article in Agricultural Engineering (December 1964, pp. 672–673)...
 13.4.59SE: An article in Communications of the ACM [(1987, Vol. 30(5), pp. 53–...
 13.4.60SE: An article in Nature Genetics [(2003, Vol. 34(1), pp. 85–90)], “Tre...
 13.4.61SE: Consider an ANOVA situation with a = 5 treatments.Let and , and sup...
 13.4.62SE: Consider an ANOVA situation with a = 4 means . Suppose that , n = 4...
 13.4.63SE: An article in Marine Biology [“Allozymes an Morphometric Characters...
 13.4.64SE: An article in Bioresource Technology [“Preliminary Tests on Nisin a...
 13.4.65SE: Reconsider Exercise 139 in which the effect of different coating t...
 13.4.66SE: An article in Journal of Hazardous Materials [“Toxicity Assessment ...
 13.4.67MEE: Show that in the fixedeffects model analysis of variance How would...
 13.4.68MEE: Consider testing the equality of the means of two normal population...
 13.4.69MEE: Consider the ANOVA with a = 2 treatments. Show that the MSE in this...
 13.4.70MEE: Show that the variance of the linear combination
 13.4.71MEE: In a fixedeffects model, suppose that there are n observations for...
 13.4.72MEE: Consider the singlefactor completely randomized design with a trea...
 13.4.73MEE: Consider the singlefactor completely randomized design. Show that ...
 13.4.74MEE: Consider the randomeffects model for the singlefactor completely ...
 13.4.75MEE: Consider a randomeffects model for the singlefactor completely ra...
 13.4.76MEE: Consider the fixedeffects model of the completely randomized singl...
 13.4.77MEE: Sample Size Determination. In the singlefactor completely randomiz...
Solutions for Chapter 13.4: Applied Statistics and Probability for Engineers 6th Edition
Full solutions for Applied Statistics and Probability for Engineers  6th Edition
ISBN: 9781118539712
Solutions for Chapter 13.4
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Acceptance region
In hypothesis testing, a region in the sample space of the test statistic such that if the test statistic falls within it, the null hypothesis cannot be rejected. This terminology is used because rejection of H0 is always a strong conclusion and acceptance of H0 is generally a weak conclusion

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

Bivariate normal distribution
The joint distribution of two normal random variables

Center line
A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.

Coeficient of determination
See R 2 .

Conditional probability density function
The probability density function of the conditional probability distribution of a continuous random variable.

Consistent estimator
An estimator that converges in probability to the true value of the estimated parameter as the sample size increases.

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

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.

Cook’s distance
In regression, Cook’s distance is a measure of the inluence of each individual observation on the estimates of the regression model parameters. It expresses the distance that the vector of model parameter estimates with the ith observation removed lies from the vector of model parameter estimates based on all observations. Large values of Cook’s distance indicate that the observation is inluential.

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.

Critical region
In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.

Distribution function
Another name for a cumulative distribution function.

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.

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

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

False alarm
A signal from a control chart when no assignable causes are present

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

Harmonic mean
The harmonic mean of a set of data values is the reciprocal of the arithmetic mean of the reciprocals of the data values; that is, h n x i n i = ? ? ? ? ? = ? ? 1 1 1 1 g .