- 6-7.6-63: Construct a normal probability plot of the piston ring diameter dat...
- 6-7.6-64: Construct a normal probability plot of the insulating fluid breakdo...
- 6-7.6-65: Construct a normal probability plot of the visual accommodation dat...
- 6-7.6-66: Construct a normal probability plot of the O-ring joint temperature...
- 6-7.6-67: Construct a normal probability plot of the octane rating data in Ex...
- 6-7.6-68: Construct a normal probability plot of the cycles to failure data i...
- 6-7.6-69: Construct a normal probability plot of the wine quality rating data...
- 6-7.6-70: Construct a normal probability plot of the suspended solids concent...
- 6-7.6-71: Construct two normal probability plots for the height data in Exerc...
- 6-7.6-72: . It is possible to obtain a quick and dirty estimate of the mean o...
Solutions for Chapter 6-7: PROBABILITY PLOTS
Full solutions for Applied Statistics and Probability for Engineers | 3rd Edition
Additivity property of x 2
If two independent random variables X1 and X2 are distributed as chi-square with v1 and v2 degrees of freedom, respectively, Y = + X X 1 2 is a chi-square random variable with u = + v v 1 2 degrees of freedom. This generalizes to any number of independent chi-square random variables.
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
A qualitative characteristic of an item or unit, usually arising in quality control. For example, classifying production units as defective or nondefective results in attributes data.
Any test of signiicance based on the chi-square distribution. The most common chi-square 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
Components of variance
The individual components of the total variance that are attributable to speciic sources. This usually refers to the individual variance components arising from a random or mixed model analysis of variance.
The probability of an event given that the random experiment produces an outcome in another event.
Conditional probability density function
The probability density function of the conditional probability distribution of a continuous random variable.
Conditional probability mass function
The probability mass function of the conditional probability distribution of a discrete random variable.
When a factorial experiment is run in blocks and the blocks are too small to contain a complete replicate of the experiment, one can run a fraction of the replicate in each block, but this results in losing information on some effects. These effects are linked with or confounded with the blocks. In general, when two factors are varied such that their individual effects cannot be determined separately, their effects are said to be confounded.
A correction factor used to improve the approximation to binomial probabilities from a normal distribution.
Formulas used to determine the number of elements in sample spaces and events.
A measure of association between two random variables obtained as the expected value of the product of the two random variables around their means; that is, Cov(X Y, ) [( )( )] =? ? E X Y ? ? X Y .
Defects-per-unit control chart
See U chart
The response variable in regression or a designed experiment.
Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.
A type of experimental design in which every level of one factor is tested in combination with every level of another factor. In general, in a factorial experiment, all possible combinations of factor levels are tested.
A signal from a control chart when no assignable causes are present
Fraction defective control chart
See P chart
A function that is used to determine properties of the probability distribution of a random variable. See Moment-generating function
Geometric random variable
A discrete random variable that is the number of Bernoulli trials until a success occurs.