 12.5.69E: Consider the gasoline mileage data in Exercise 1211.(a) What propo...
 12.5.70E: Consider the electric power consumption data in Exercise 1210.(a) ...
 12.5.71E: Consider the regression model for the NFL data in Exercise 1221.(a...
 12.5.72E: Consider the regression model for the heattreating data in Exercis...
 12.5.73E: Consider the regression model fi t to the Xray inspection data in ...
 12.5.74E: Consider the regression model fi t to the arsenic data in Exercise ...
 12.5.75E: Consider the regression model fi t to the coal and limestone mixtur...
 12.5.76E: Consider the regression model fit to the nisin extraction data in E...
 12.5.77E: Consider the regression model fit to the gray range modulation data...
 12.5.78E: Consider the stack loss data in Exercise 1220.(a) What proportion ...
 12.5.79E: Consider the bearing wear data in Exercise 1223.(a) Find the value...
 12.5.81E: Consider the semiconductor HFE data in Exercise 1213.(a) Plot the ...
 12.5.82E: Consider the regression model for the NHL data from Exercise 1222....
 12.5.83E: The diagonal elements of the hat matrix are often used to denote le...
Solutions for Chapter 12.5: Applied Statistics and Probability for Engineers 6th Edition
Full solutions for Applied Statistics and Probability for Engineers  6th Edition
ISBN: 9781118539712
Solutions for Chapter 12.5
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. Since 14 problems in chapter 12.5 have been answered, more than 149255 students have viewed full stepbystep solutions from this chapter. This 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. Chapter 12.5 includes 14 full stepbystep solutions.

`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).

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

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.

Analytic study
A study in which a sample from a population is used to make inference to a future population. Stability needs to be assumed. See Enumerative study

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

Bivariate normal distribution
The joint distribution of two normal random variables

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.

Chisquare test
Any test of signiicance based on the chisquare distribution. The most common chisquare tests are (1) testing hypotheses about the variance or standard deviation of a normal distribution and (2) testing goodness of it of a theoretical distribution to sample data

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

Correlation coeficient
A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).

Cumulative sum control chart (CUSUM)
A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t

Decision interval
A parameter in a tabular CUSUM algorithm that is determined from a tradeoff between false alarms and the detection of assignable causes.

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

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

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.

Exponential random variable
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.

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

Fraction defective control chart
See P chart

Frequency distribution
An arrangement of the frequencies of observations in a sample or population according to the values that the observations take on