Solutions for Chapter SECTION IV: CASH DISCOUNTS AND TERMS OF SALE

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

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

The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.

An attribute control chart that plots the total number of defects per unit in a subgroup. Similar to a defects-per-unit or U chart.

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

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.

The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.

An expression sometimes used for nonlinear regression models or polynomial regression models.

A parameter in a tabular CUSUM algorithm that is determined from a trade-off between false alarms and the detection of assignable causes.

See U chart

Another name for a probability density function

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

The numerical value of a point estimator.

A subset of a 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.

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

A method used in regression analysis to conduct a hypothesis test for the additional contribution of one or more variables to a model.

The geometric mean of a set of n positive data values is the nth root of the product of the data values; that is, g x i n i n = ( ) = / w 1 1 .