 4.7.1BSC: Simulating Dice When two dice are rolled, the total is between 2 an...
 4.7.2BSC: Simulating dice Assume that you have access to a computer that can ...
 4.7.3BSC: Simulating Birthdays A student wants to conduct the simulation desc...
 4.7.4BSC: Simulating coin Flips One student conducted the simulation describe...
 4.7.5BSC: Describe the simulation procedure. (For example, to simulate 10 bir...
 4.7.6BSC: 6BSC: Describe the simulation procedure. (For example, to simulate ...
 4.7.7BSC: Describe the simulation procedure. (For example, to simulate 10 bir...
 4.7.8BSC: Describe the simulation procedure. (For example, to simulate 10 bir...
 4.7.9BSC: Develop a simulation using a TI83/84 Plus calculator, STATDISK, Mi...
 4.7.10BSC: Develop a simulation using a TI83/84 Plus calculator, STATDISK, Mi...
 4.7.11BSC: Develop a simulation using a TI83/84 Plus calculator, STATDISK, Mi...
 4.7.12BSC: Develop a simulation using a TI83/84 Plus calculator, STATDISK, Mi...
 4.7.13BSC: Probability of a Run of Three Use a simulation approach to find the...
 4.7.14BSC: Probability of a Run of Four Use a simulation approach to find the ...
 4.7.15BSC: GenderSelection Method As of this writing, the latest results avai...
 4.7.16BSC: Nasonex Treatment Analysis Nasonex is a nasal spray used to treat a...
 4.7.17BSC: Simulating the Monty Hall problem that once attracted much attentio...
 4.7.18BB: Simulating Birthdaysa. Develop a simulation for finding the probabi...
 4.7.19BB: Genetics: Simulating Population control A classical probability pro...
Solutions for Chapter 4.7: Elementary Statistics 12th Edition
Full solutions for Elementary Statistics  12th Edition
ISBN: 9780321836960
Solutions for Chapter 4.7
Get Full SolutionsSince 19 problems in chapter 4.7 have been answered, more than 390645 students have viewed full stepbystep solutions from this chapter. Elementary Statistics was written by and is associated to the ISBN: 9780321836960. This textbook survival guide was created for the textbook: Elementary Statistics, edition: 12. Chapter 4.7 includes 19 full stepbystep solutions. This expansive textbook survival guide covers the following chapters and their solutions.

Attribute
A qualitative characteristic of an item or unit, usually arising in quality control. For example, classifying production units as defective or nondefective results in attributes data.

Binomial random variable
A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.

Bivariate normal distribution
The joint distribution of two normal random variables

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.

Coeficient of determination
See R 2 .

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

Contingency table.
A tabular arrangement expressing the assignment of members of a data set according to two or more categories or classiication criteria

Control chart
A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the incontrol 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 incontrol, or free from assignable causes. Points beyond the control limits indicate an outofcontrol process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.

Correction factor
A term used for the quantity ( / )( ) 1 1 2 n xi i n ? = that is subtracted from xi i n 2 ? =1 to give the corrected sum of squares deined as (/ ) ( ) 1 1 2 n xx i x i n ? = i ? . The correction factor can also be written as nx 2 .

Covariance matrix
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 offdiagonal elements are the covariances between Xi and Xj . Also called the variancecovariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.

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

Defectsperunit control chart
See U chart

Degrees of freedom.
The number of independent comparisons that can be made among the elements of a sample. The term is analogous to the number of degrees of freedom for an object in a dynamic system, which is the number of independent coordinates required to determine the motion of the object.

Designed experiment
An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

Dispersion
The amount of variability exhibited by data

Distribution free method(s)
Any method of inference (hypothesis testing or conidence interval construction) that does not depend on the form of the underlying distribution of the observations. Sometimes called nonparametric method(s).

Eficiency
A concept in parameter estimation that uses the variances of different estimators; essentially, an estimator is more eficient than another estimator if it has smaller variance. When estimators are biased, the concept requires modiication.

Enumerative study
A study in which a sample from a population is used to make inference to the population. See Analytic study

Error mean square
The error sum of squares divided by its number of degrees of freedom.

Firstorder model
A model that contains only irstorder terms. For example, the irstorder response surface model in two variables is y xx = + ?? ? ? 0 11 2 2 + + . A irstorder model is also called a main effects model