- 14-3.1: Define simulation technique.
- 14-3.2: Have simulation techniques been used for very many years?
- 14-3.3: Is it cost-effective to do simulation testing on some things such a...
- 14-3.4: Why might simulation testing be better than real-life testing? Give...
- 14-3.5: When did physicists develop computer simulation techniques to study...
- 14-3.6: When could simulations be misleading or harmful? Give examples.
- 14-3.7: Could simulations have prevented previous disasters such as the Hin...
- 14-3.8: What discipline is simulation theory based on?
- 14-3.1: Define simulation techniques.
- 14-3.2: Define simulation techniques.
- 14-3.3: Who is responsible for the development of modern simulation techniq...
- 14-3.4: What role does the computer play in simulation?
- 14-3.5: What are the steps in the simulation of an experiment?
- 14-3.6: What purpose do random numbers play in simulation?
- 14-3.7: What happens when the number of repetitions is increased?
- 14-3.8: For Exercises 8 through 13, explain how each experiment can be simu...
- 14-3.9: For Exercises 8 through 13, explain how each experiment can be simu...
- 14-3.10: For Exercises 8 through 13, explain how each experiment can be simu...
- 14-3.11: For Exercises 8 through 13, explain how each experiment can be simu...
- 14-3.12: For Exercises 8 through 13, explain how each experiment can be simu...
- 14-3.13: For Exercises 8 through 13, explain how each experiment can be simu...
- 14-3.14: For Exercises 14 through 21, use random numbers to simulate the exp...
- 14-3.15: For Exercises 14 through 21, use random numbers to simulate the exp...
- 14-3.16: For Exercises 14 through 21, use random numbers to simulate the exp...
- 14-3.17: For Exercises 14 through 21, use random numbers to simulate the exp...
- 14-3.18: For Exercises 14 through 21, use random numbers to simulate the exp...
- 14-3.19: For Exercises 14 through 21, use random numbers to simulate the exp...
- 14-3.20: For Exercises 14 through 21, use random numbers to simulate the exp...
- 14-3.21: For Exercises 14 through 21, use random numbers to simulate the exp...
- 14-3.22: Which would be easier to simulate with random numbers, baseball or ...
- 14-3.23: Explain how cards can be used to generate random numbers.
- 14-3.24: Explain how a pair of dice can be used to generate random numbers.
Solutions for Chapter 14-3: Sampling and Simulation
Full solutions for Elementary Statistics: A Step by Step Approach | 7th Edition
Analysis of variance (ANOVA)
A method of decomposing the total variability in a set of observations, as measured by the sum of the squares of these observations from their average, into component sums of squares that are associated with speciic deined sources of variation
The arithmetic mean of a set of numbers x1 , x2 ,…, xn is their sum divided by the number of observations, or ( / )1 1 n xi t n ? = . The arithmetic mean is usually denoted by x , and is often called the average
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.
An equation for a conditional probability such as PA B ( | ) in terms of the reverse conditional probability PB A ( | ).
In experimental design, a group of experimental units or material that is relatively homogeneous. The purpose of dividing experimental units into blocks is to produce an experimental design wherein variability within blocks is smaller than variability between blocks. This allows the factors of interest to be compared in an environment that has less variability than in an unblocked experiment.
A chart used to organize the various potential causes of a problem. Also called a ishbone diagram.
The tendency of data to cluster around some value. Central tendency is usually expressed by a measure of location such as the mean, median, or mode.
Conditional probability density function
The probability density function of the conditional probability distribution of a continuous random variable.
If it is possible to write a probability statement of the form PL U ( ) ? ? ? ? = ?1 where L and U are functions of only the sample data and ? is a parameter, then the interval between L and U is called a conidence interval (or a 100 1( )% ? ? conidence interval). The interpretation is that a statement that the parameter ? lies in this interval will be true 100 1( )% ? ? of the times that such a statement is made
A square matrix that contains the correlations among a set of random variables, say, XX X 1 2 k , ,…, . The main diagonal elements of the matrix are unity and the off-diagonal elements rij are the correlations between Xi and Xj .
A subset of effects in a fractional factorial design that deine the aliases in the design.
Another name for a probability density function
Another name for a cumulative distribution function.
A study in which a sample from a population is used to make inference to the population. See Analytic study
Exponential random variable
A series of tests in which changes are made to the system under study
Any test of signiicance involving the F distribution. The most common F-tests are (1) testing hypotheses about the variances or standard deviations of two independent normal distributions, (2) testing hypotheses about treatment means or variance components in the analysis of variance, and (3) testing signiicance of regression or tests on subsets of parameters in a regression model.
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.
Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.
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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