- 6.7.1E: A crayon manufacturer is comparing the effects of two kinds of yell...
- 6.7.2E: In a study of the relationship of the shape of a tablet to its diss...
- 6.7.3E: The article “Influence of Penetration Rate on Penetrometer Resistan...
- 6.7.4E: The article "Time Series Analysis for Construction Productivity Exp...
- 6.7.5E: The Mastic tree (Pistacia lentiscus) is used in reforestation effor...
- 6.7.6E: Two weights, each labeled as weighing 100 g, are each weighed sever...
- 6.7.7E: It is thought that a new process for producing a certain chemical m...
- 6.7.8E: The article "Effects of Aerosol Species on Atmospheric Visibility i...
- 6.7.9E: The article “Wind-Uplift Capacity of Residential Wood Roof-Sheathin...
- 6.7.10E: The article "Magma Interaction Processes Inferred from Fe-Ti Oxide ...
- 6.7.11E: The article "Structural Performance of Rounded Dovetail Connections...
- 6.7.12E: The article "Variance Reduction Techniques: Experimental Comparison...
- 6.7.13E: In an experiment to test the effectiveness of a new sleeping aid, a...
- 6.7.14E: Refer to Exercise 11 in Section 5.6. Can you conclude that the mean...
- 6.7.15E: Refer to Exercise 12 in Section 5.6. Can you conclude that the mean...
- 6.7.16E: The following MINITAB output presents the results of a hypothesis t...
- 6.7.17E: The following MINITAB output presents the results of a hypothesis t...
Solutions for Chapter 6.7: Statistics for Engineers and Scientists 4th Edition
Full solutions for Statistics for Engineers and Scientists | 4th Edition
Adjusted R 2
A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.
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
An equation for a conditional probability such as PA B ( | ) in terms of the reverse conditional probability PB A ( | ).
Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.
The joint probability distribution of two random variables.
A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.
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.
The mean of the conditional probability distribution of a random variable.
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
An estimator that converges in probability to the true value of the estimated parameter as the sample size increases.
Formulas used to determine the number of elements in sample spaces and events.
Cumulative distribution function
For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.
Defects-per-unit control chart
See U chart
Another name for a probability density function
A matrix that provides the tests that are to be conducted in an experiment.
Error sum of squares
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.
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.
Fixed factor (or fixed effect).
In analysis of variance, a factor or effect is considered ixed if all the levels of interest for that factor are included in the experiment. Conclusions are then valid about this set of levels only, although when the factor is quantitative, it is customary to it a model to the data for interpolating between these levels.
Fractional factorial experiment
A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.