Applied Statistics and Probability for Engineers 3rd Edition - Solutions by Chapter

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

The average number of samples taken in a process monitoring or inspection scheme until the scheme signals that the process is operating at a level different from the level in which it began.

A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

A distribution with two modes

A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.

The probability density function of the conditional probability distribution of a continuous random variable.

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

A method to derive the probability density function of the sum of two independent random variables from an integral (or sum) of probability density (or mass) functions.

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

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

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

See U chart

The number of independent comparisons that can be made among the elements of a sample. The term is analogous to the number of degrees of freedom for an object in a dynamic system, which is the number of independent coordinates required to determine the motion of the object.

The amount of variability exhibited by data

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).

A study in which a sample from a population is used to make inference to the population. See Analytic study

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

An analysis of how the variance of the random variable that represents that output of a system depends on the variances of the inputs. A formula exists when the output is a linear function of the inputs and the formula is simpliied if the inputs are assumed to be independent.

In analysis of variance, this is the portion of total variability that is due to the random component in the data. It is usually based on replication of observations at certain treatment combinations in the experiment. It is sometimes called the residual sum of squares, although this is really a better term to use only when the sum of squares is based on the remnants of a model-itting process and not on replication.

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.