 143.1: Define simulation technique.
 143.2: Have simulation techniques been used for very many years?
 143.3: Is it costeffective to do simulation testing on some things such a...
 143.4: Why might simulation testing be better than reallife testing? Give...
 143.5: When did physicists develop computer simulation techniques to study...
 143.6: When could simulations be misleading or harmful? Give examples.
 143.7: Could simulations have prevented previous disasters such as the Hin...
 143.8: What discipline is simulation theory based on?
 143.1: Define simulation techniques.
 143.2: Define simulation techniques.
 143.3: Who is responsible for the development of modern simulation techniq...
 143.4: What role does the computer play in simulation?
 143.5: What are the steps in the simulation of an experiment?
 143.6: What purpose do random numbers play in simulation?
 143.7: What happens when the number of repetitions is increased?
 143.8: For Exercises 8 through 13, explain how each experiment can be simu...
 143.9: For Exercises 8 through 13, explain how each experiment can be simu...
 143.10: For Exercises 8 through 13, explain how each experiment can be simu...
 143.11: For Exercises 8 through 13, explain how each experiment can be simu...
 143.12: For Exercises 8 through 13, explain how each experiment can be simu...
 143.13: For Exercises 8 through 13, explain how each experiment can be simu...
 143.14: For Exercises 14 through 21, use random numbers to simulate the exp...
 143.15: For Exercises 14 through 21, use random numbers to simulate the exp...
 143.16: For Exercises 14 through 21, use random numbers to simulate the exp...
 143.17: For Exercises 14 through 21, use random numbers to simulate the exp...
 143.18: For Exercises 14 through 21, use random numbers to simulate the exp...
 143.19: For Exercises 14 through 21, use random numbers to simulate the exp...
 143.20: For Exercises 14 through 21, use random numbers to simulate the exp...
 143.21: For Exercises 14 through 21, use random numbers to simulate the exp...
 143.22: Which would be easier to simulate with random numbers, baseball or ...
 143.23: Explain how cards can be used to generate random numbers.
 143.24: Explain how a pair of dice can be used to generate random numbers.
Solutions for Chapter 143: Sampling and Simulation
Full solutions for Elementary Statistics: A Step by Step Approach  7th Edition
ISBN: 9780073534978
Solutions for Chapter 143: Sampling and Simulation
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. Since 32 problems in chapter 143: Sampling and Simulation have been answered, more than 6305 students have viewed full stepbystep solutions from this chapter. Chapter 143: Sampling and Simulation includes 32 full stepbystep solutions. Elementary Statistics: A Step by Step Approach was written by Patricia and is associated to the ISBN: 9780073534978. This textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach, edition: 7.

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

Arithmetic mean
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

Assignable cause
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.

Average
See Arithmetic mean.

Bayes’ theorem
An equation for a conditional probability such as PA B (  ) in terms of the reverse conditional probability PB A (  ).

Block
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.

Causeandeffect diagram
A chart used to organize the various potential causes of a problem. Also called a ishbone diagram.

Central tendency
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.

Conidence interval
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

Correlation matrix
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 offdiagonal elements rij are the correlations between Xi and Xj .

Deining relation
A subset of effects in a fractional factorial design that deine the aliases in the design.

Density function
Another name for a probability density function

Distribution function
Another name for a cumulative distribution function.

Enumerative study
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

Ftest
Any test of signiicance involving the F distribution. The most common Ftests 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.

Generator
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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