- Chapter 1:
- Chapter 1: What Is Statistics?
- Chapter 10:
- Chapter 10: Hypothesis Testing
- Chapter 11:
- Chapter 11: Linear Models and Estimation by Least Squares
- Chapter 12:
- Chapter 12: Considerations in Designing Experiments
- Chapter 13:
- Chapter 13: The Analysis of Variance
- Chapter 14:
- Chapter 14: Analysis of Categorical Data
- Chapter 15:
- Chapter 15: Nonparametric Statistics
- Chapter 16:
- Chapter 16: Introduction to Bayesian Methods for Inference
- Chapter 2:
- Chapter 2: Probability
- Chapter 3:
- Chapter 3: Discrete Random Variables and Their Probability Distributions
- Chapter 4:
- Chapter 4: Continuous Variables and Their Probability Distributions
- Chapter 5:
- Chapter 5: Multivariate Probability Distributions
- Chapter 6:
- Chapter 6: Functions of Random Variables
- Chapter 7:
- Chapter 7: Sampling Distributions and the Central Limit Theorem
- Chapter 8:
- Chapter 8: Estimation
- Chapter 9:
- Chapter 9: Properties of Point Estimators and Methods of Estimation
Mathematical Statistics with Applications 7th Edition - Solutions by Chapter
Full solutions for Mathematical Statistics with Applications | 7th Edition
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
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.
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.
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.
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.
A probability distribution for a continuous random variable.
A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the in-control value of the parameter that is being monitored and lower and upper control limits. The control limits are determined by statistical criteria and are not arbitrary, nor are they related to speciication limits. If sample points fall within the control limits, the process is said to be in-control, or free from assignable causes. Points beyond the control limits indicate an out-of-control process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.
A method to derive the probability density function of the sum of two independent random variables from an integral (or sum) of probability density (or mass) functions.
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.
Another name for factors that are arranged in a factorial experiment.
A parameter in a tabular CUSUM algorithm that is determined from a trade-off between false alarms and the detection of assignable causes.
Used in statistical quality control, a defect is a particular type of nonconformance to speciications or requirements. Sometimes defects are classiied into types, such as appearance defects and functional defects.
W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.
Error mean square
The error sum of squares divided by its number of degrees of freedom.
A subset of a sample space.
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 method of variable selection in regression, where variables are inserted one at a time into the model until no other variables that contribute signiicantly to the model can be found.
Fraction defective control chart
See P chart
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 .
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