 144.141: In his book (Design and Analysis of Experiments, 5th edition, 2001 ...
 144.142: An engineer who suspects that the surface finish of metal parts is ...
 144.143: 143. An article in Industrial Quality Control (1956, pp. 58) descr...
 144.144: An experiment was conducted to determine whether either firing temp...
 144.145: Continuation of Exercise 144. Using Fishers LSD method, investigat...
 144.146: Johnson and Leone (Statistics and Experimental Design in Engineerin...
 144.147: 147. Consider a twofactor factorial experiment. Develop a formula...
 144.148: An article in the Journal of Testing and Evaluation (Vol. 16, no. 6...
 144.149: 149. An article in the IEEE Transactions on Electron Devices (Nove...
 144.1410: Consider the experiment described in Exercise 149. Use Fishers LSD...
Solutions for Chapter 144: TWOFACTOR FACTORIAL EXPERIMENTS
Full solutions for Applied Statistics and Probability for Engineers  3rd Edition
ISBN: 9780471204541
Solutions for Chapter 144: TWOFACTOR FACTORIAL EXPERIMENTS
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2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

All possible (subsets) regressions
A method of variable selection in regression that examines all possible subsets of the candidate regressor variables. Eficient computer algorithms have been developed for implementing all possible regressions

Alternative hypothesis
In statistical hypothesis testing, this is a hypothesis other than the one that is being tested. The alternative hypothesis contains feasible conditions, whereas the null hypothesis speciies conditions that are under test

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

Backward elimination
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

Bernoulli trials
Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

Bias
An effect that systematically distorts a statistical result or estimate, preventing it from representing the true quantity of interest.

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

Completely randomized design (or experiment)
A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order.

Conditional variance.
The variance of the conditional probability distribution of a random variable.

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

Critical value(s)
The value of a statistic corresponding to a stated signiicance level as determined from the sampling distribution. For example, if PZ z PZ ( )( .) . ? =? = 0 025 . 1 96 0 025, then z0 025 . = 1 9. 6 is the critical value of z at the 0.025 level of signiicance. Crossed factors. Another name for factors that are arranged in a factorial experiment.

Defect concentration diagram
A quality tool that graphically shows the location of defects on a part or in a process.

Dependent variable
The response variable in regression or a designed experiment.

Distribution free method(s)
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).

Error propagation
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.

F distribution.
The distribution of the random variable deined as the ratio of two independent chisquare random variables, each divided by its number of degrees of freedom.

Geometric mean.
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 .

Geometric random variable
A discrete random variable that is the number of Bernoulli trials until a success occurs.