 1612.1643: The diameter of fuse pins used in an aircraft engine application is...
 1612.1644: Rework Exercise 1643 with and S charts
 1612.1645: 1645. Plastic bottles for liquid laundry detergent are formed by b...
 1612.1646: Cover cases for a personal computer are manufactured by injection m...
 1612.1647: 1647. Consider the data in Exercise 1646. (a) Using all the data,...
 1612.1648: Suppose that a process is in control and an chart is used with a sa...
 1612.1649: 1649. Consider the control chart for individuals with 3sigma limits.
 1612.1650: Consider a control chart for individuals, applied to a continuous 2...
 1612.1651: 1651. The depth of a keyway is an important part quality character...
 1612.1652: A process is controlled by a P chart using samples of size 100. The...
 1612.1653: 1653. Suppose the average number of defects in a unit is known to ...
 1612.1654: Suppose the average number of defects in a unit is X known to be 10...
 1612.1655: Suppose that an control chart with 2sigma limits is used to contro...
 1612.1656: Consider the control chart with 2sigma limits in Exercise 1650. (...
 1612.1657: Suppose a process has a PCR 2, but the mean is exactly three standa...
 1612.1658: Consider the hardness measurement data in Exercise 169. Set up a C...
 1612.1659: Consider the data in Exercise 1610. Set up a CUSUM scheme for this...
 1612.1660: Reconsider the data in Exercise 1612. Construct a CUSUM control ch...
 1612.1661: Suppose a process is in control, and 3sigma control limits are in ...
 1612.1662: Consider an control chart with ksigma control limits. Develop a ge...
 1612.1663: Suppose that an chart is used to control a normally distributed pro...
 1612.1664: Suppose a P chart with center line at with ksigma control limits is...
 1612.1665: Suppose that a P chart with center line at and ksigma control limi...
 1612.1666: A process is controlled by a P chart using samples of size 100. The...
 1612.1667: Consider a process where specifications on a quality characteristic...
 1612.1668: The NP Control Chart. An alternative to the control chart for fract...
 1612.1669: The EWMA Control Chart. The exponentially weighted moving average (...
 1612.1670: Standardized Control Chart. Consider the P chart with the usual 3s...
 1612.1671: Unequal Sample Sizes. One application of the standardized control c...
Solutions for Chapter 1612: IMPLEMENTING SPC
Full solutions for Applied Statistics and Probability for Engineers  3rd Edition
ISBN: 9780471204541
Solutions for Chapter 1612: IMPLEMENTING SPC
Get Full SolutionsChapter 1612: IMPLEMENTING SPC includes 29 full stepbystep solutions. Applied Statistics and Probability for Engineers was written by and is associated to the ISBN: 9780471204541. 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: 3. Since 29 problems in chapter 1612: IMPLEMENTING SPC have been answered, more than 18162 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).

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

Bivariate distribution
The joint probability distribution of two random variables.

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

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 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

Conidence interval
If it is possible to write a probability statement of the form PL U ( ) ? ? ? ? = ?1 where L and U are functions of only the sample data and ? is a parameter, then the interval between L and U is called a conidence interval (or a 100 1( )% ? ? conidence interval). The interpretation is that a statement that the parameter ? lies in this interval will be true 100 1( )% ? ? of the times that such a statement is made

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

Continuous uniform random variable
A continuous random variable with range of a inite interval and a constant probability density function.

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).

Crossed factors
Another name for factors that are arranged in a factorial experiment.

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

Designed experiment
An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

Discrete distribution
A probability distribution for a discrete random variable

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

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.

Event
A subset of a sample space.

Fraction defective control chart
See P chart

Generator
Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.

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 .