- 3.8.141E: Suppose that X has a hypergeometric distribution with N = 100, n = ...
- 3.8.142E: Suppose that X has a hypergeometric distribution with N = 20, n = 4...
- 3.8.143E: Suppose that X has a hypergeometric distribution with N = 10, n = 3...
- 3.8.144E: A batch contains 36 bacteria cells and 12 of the cells are not capa...
- 3.8.145E: A research study uses 800 men under the age of 55. Suppose that 30%...
- 3.8.146E: Printed circuit cards are placed in a functional test after being p...
- 3.8.147E: The analysis of results from a leaf transmutation experiment (turni...
- 3.8.148E: A state runs a lottery in which six numbers are randomly selected f...
- 3.8.149E: A slitter assembly contains 48 blades. Five blades are selected at ...
- 3.8.150E: Calculate the finite population corrections(a) For Exercises 3-141 ...
- 3.8.151E: Consider the visits that result in leave without being seen (LWBS) ...
- 3.8.152E: Calculate the finite population corrections(a) For Exercises 3-141 ...
- 3.8.153E: Consider the semiconductor wafer data in Table 2-1. Suppose that 10...
- 3.8.154E: Suppose that a healthcare provider selects 20 patients randomly (wi...
- 3.8.155E: Suppose that lesions are present at 5 sites among 50 in a patient. ...
- 3.8.156E: A utility company might offer electrical rates based on time-of-day...
Solutions for Chapter 3.8: Applied Statistics and Probability for Engineers 6th Edition
Full solutions for Applied Statistics and Probability for Engineers | 6th Edition
a-error (or a-risk)
In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II error).
In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.
Bivariate normal distribution
The joint distribution of two normal random variables
A chart used to organize the various potential causes of a problem. Also called a ishbone diagram.
A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.
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 mass function
The probability mass function of the conditional probability distribution of a discrete random variable.
The variance of the conditional probability distribution of a random variable.
Another term for the conidence coeficient.
A correction factor used to improve the approximation to binomial probabilities from a normal distribution.
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
A parameter in a tabular CUSUM algorithm that is determined from a trade-off between false alarms and the detection of assignable causes.
A subset of effects in a fractional factorial design that deine the aliases in the design.
The amount of variability exhibited by data
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.
A model to relate a response to one or more regressors or factors that is developed from data obtained from the system.
Error of estimation
The difference between an estimated value and the true value.
A property of a collection of events that indicates that their union equals the sample space.
The expected value of a random variable X is its long-term average or mean value. In the continuous case, the expected value of X is E X xf x dx ( ) = ?? ( ) ? ? where f ( ) x is the density function of the random variable X.
Geometric random variable
A discrete random variable that is the number of Bernoulli trials until a success occurs.