- 11.R11.1: Testing a genetic model Biologists wish to cross pairs of tobacco p...
- 11.R11.2: Sorry, no chi-square We would prefer to learn from teachers who kno...
- 11.R11.3: Stress and heart attacks You read a newspaper article that describe...
- 11.R11.4: Sexy magazine ads? Researchers looked at 1509 full-page ads that sh...
- 11.R11.5: Popular kids Who were the popular kids at your elementary school? D...
- 11.T11.1: Section I: Multiple Choice Select the best answer for each question...
- 11.T11.2: Section I: Multiple Choice Select the best answer for each question...
- 11.T11.3: Section I: Multiple Choice Select the best answer for each question...
- 11.T11.4: Section I: Multiple Choice Select the best answer for each question...
- 11.T11.5: Section I: Multiple Choice Select the best answer for each question...
- 11.T11.6: Section I: Multiple Choice Select the best answer for each question...
- 11.T11.7: Section I: Multiple Choice Select the best answer for each question...
- 11.T11.8: Section I: Multiple Choice Select the best answer for each question...
- 11.T11.9: Section I: Multiple Choice Select the best answer for each question...
- 11.T11.10: Section I: Multiple Choice Select the best answer for each question...
- 11.T11.11: Section II: Free Response Show all your work. Indicate clearly the ...
- 11.T11.12: Section II: Free Response Show all your work. Indicate clearly the ...
- 11.T11.13: Section II: Free Response Show all your work. Indicate clearly the ...
Solutions for Chapter 11: Inference for Ditribution of Categorical Data
Full solutions for The Practice of Statistics | 5th Edition
2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.
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.
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
The portion of the variability in a set of observations that can be traced to speciic causes, such as operators, materials, or equipment. Also called a special cause.
See Arithmetic mean.
Average run length, or ARL
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
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.
Continuous uniform random variable
A continuous random variable with range of a inite interval and a constant probability density function.
A square matrix that contains the variances and covariances among a set of random variables, say, X1 , X X 2 k , , … . The main diagonal elements of the matrix are the variances of the random variables and the off-diagonal elements are the covariances between Xi and Xj . Also called the variance-covariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.
Cumulative distribution function
For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.
Cumulative sum control chart (CUSUM)
A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t
An expression sometimes used for nonlinear regression models or polynomial regression models.
Discrete random variable
A random variable with a inite (or countably ininite) range.
Another name for a cumulative distribution function.
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 series of tests in which changes are made to the system under study
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.
A function that is used to determine properties of the probability distribution of a random variable. See Moment-generating function
Goodness of fit
In general, the agreement of a set of observed values and a set of theoretical values that depend on some hypothesis. The term is often used in itting a theoretical distribution to a set of observations.
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