 15.7.59E: An X chart uses samples of size 1. The center line is at 100, and t...
 15.7.60E: An chart uses samples of size 4. The center line is at 100, and the...
 15.7.61E: Consider the control chart in Fig. 153. Suppose that the mean shif...
 15.7.62E: Consider an UCL = 14.708, LCL = 14.312, and n = 5. Suppose that the...
 15.7.63E: Consider an control chart with UCL = 242.780, LCL = 203.220, and n ...
 15.7.64E: Consider an control chart with UCL = 21.71, LCL = 18.29, and n = 6....
 15.7.65E: Consider an control chart with UCL = 37.404, LCL = 30.780, and n = ...
 15.7.66E: Consider an control chart with UCL =17.40, LCL = 12.79, and n = 3. ...
 15.7.67E: Consider an control chart with UCL = 0.0635, LCL = 0.0624, and n = ...
 15.7.68E: Consider the revised control chart in Exercise 158 with ?ˆ = 0.669...
 15.7.69E: An chart uses a sample of size 3. The center line is at 200, and th...
 15.7.70E: Consider an control chart with UCL = 24.802, LCL = 23.792, and n = ...
 15.7.71E: Consider a Pchart with subgroup size n = 50 and center line at 0.1...
 15.7.72E: Consider the U chart for printed circuit boards in Example 155. Th...
Solutions for Chapter 15.7: Applied Statistics and Probability for Engineers 6th Edition
Full solutions for Applied Statistics and Probability for Engineers  6th Edition
ISBN: 9781118539712
Solutions for Chapter 15.7
Get Full SolutionsThis textbook survival guide was created for the textbook: Applied Statistics and Probability for Engineers , edition: 6. Applied Statistics and Probability for Engineers was written by and is associated to the ISBN: 9781118539712. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 15.7 includes 14 full stepbystep solutions. Since 14 problems in chapter 15.7 have been answered, more than 173348 students have viewed full stepbystep solutions from this chapter.

`error (or `risk)
In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).

Alias
In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

Arithmetic mean
The arithmetic mean of a set of numbers x1 , x2 ,…, xn is their sum divided by the number of observations, or ( / )1 1 n xi t n ? = . The arithmetic mean is usually denoted by x , and is often called the average

Attribute control chart
Any control chart for a discrete random variable. See Variables control chart.

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

Causeandeffect diagram
A chart used to organize the various potential causes of a problem. Also called a ishbone diagram.

Central composite design (CCD)
A secondorder response surface design in k variables consisting of a twolevel factorial, 2k axial runs, and one or more center points. The twolevel factorial portion of a CCD can be a fractional factorial design when k is large. The CCD is the most widely used design for itting a secondorder model.

Completely randomized design (or experiment)
A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order.

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

Continuous distribution
A probability distribution for a continuous random variable.

Control limits
See Control chart.

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 .

Counting techniques
Formulas used to determine the number of elements in sample spaces and events.

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.

Defectsperunit control chart
See U chart

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).

Error mean square
The error sum of squares divided by its number of degrees of freedom.

Experiment
A series of tests in which changes are made to the system under study

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.

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