- 5-5.5-67: 5-67. Determine the covariance and correlation for the following jo...
- 5-5.5-68: Determine the covariance and correlation for the following joint pr...
- 5-5.5-69: 5-69. Determine the value for c and the covariance and correlation ...
- 5-5.5-70: Determine the covariance and correlation for the joint probability ...
- 5-5.5-71: 5-71. Determine the covariance and correlation for X1 and X2 in the...
- 5-5.5-72: Determine the value for c and the covariance and correlation for th...
- 5-5.5-73: 5-73. Determine the value for c and the covariance and correlation ...
- 5-5.5-74: Determine the covariance and correlation for the joint probability ...
- 5-5.5-75: 5-75. Determine the covariance and correlation for the joint probab...
- 5-5.5-76: Suppose that the correlation between X and Y is . For constants a, ...
- 5-5.5-77: The joint probability distribution is x 1 01 y 11 0 fXY (x, y) Show...
- 5-5.5-78: Suppose X and Y are independent continuous random variables. Show t...
Solutions for Chapter 5-5: COVARIANCE AND CORRELATION
Full solutions for Applied Statistics and Probability for Engineers | 3rd Edition
2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.
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
Attribute control chart
Any control chart for a discrete random variable. See Variables control chart.
An estimator for a parameter obtained from a Bayesian method that uses a prior distribution for the parameter along with the conditional distribution of the data given the parameter to obtain the posterior distribution of the parameter. The estimator is obtained from the posterior distribution.
An effect that systematically distorts a statistical result or estimate, preventing it from representing the true quantity of interest.
A distribution with two modes
Data consisting of counts or observations that can be classiied into categories. The categories may be descriptive.
Central composite design (CCD)
A second-order response surface design in k variables consisting of a two-level factorial, 2k axial runs, and one or more center points. The two-level factorial portion of a CCD can be a fractional factorial design when k is large. The CCD is the most widely used design for itting a second-order model.
Conditional probability density function
The probability density function of the conditional probability distribution of a continuous 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
A probability distribution for a continuous random variable.
In the most general usage, a measure of the interdependence among data. The concept may include more than two variables. The term is most commonly used in a narrow sense to express the relationship between quantitative variables or ranks.
Defects-per-unit control chart
See U chart
Deming’s 14 points.
A management philosophy promoted by W. Edwards Deming that emphasizes the importance of change and quality
Another name for a cumulative distribution function.
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 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.
Finite population correction factor
A term in the formula for the variance of a hypergeometric random variable.
Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.