 5.5.8CQQ: In Exercises, use the following: Five U.S. domestic flights are ran...
 5.5.5CQQ: If boys and girls are equally likely, groups of 400 births have a m...
 5.5.5RE: In Exercises , refer to the table in the margin. The random variabl...
 5.5.6CQQ: In Exercises, use the following: Five U.S. domestic flights are ran...
 5.5.10CQQ: In Exercises, use the following: Five U.S. domestic flights are ran...
 5.5.6RE: In Exercises , refer to the table in the margin. The random variabl...
 5.5.7CQQ: In Exercises, use the following: Five U.S. domestic flights are ran...
 5.5.16BSC: Use the Poisson distribution to find the indicated probabilities.Ch...
 5.5.1BSC: Notation In analyzing hits by Vl buzz bombs in World War II, South...
 5.5.1CQQ: Is a probability distribution defined if the only possible values o...
 5.5.1CRE: Weekly Instruction Time The Organization for Economic Cooperation a...
 5.5.1RE: In Exercises, assume that 40% of the population has brown eyes (bas...
 5.5.2BSC: Tornadoes During a recent 46year period, New York State had a tota...
 5.5.2CQQ: There are 100 questions from an SAT test, and they are all multiple...
 5.5.2CRE: Ohio Pick 4 In Ohio’s Pick 4 game, you pay $1 to select a sequence ...
 5.5.2RE: In Exercises, assume that 40% of the population has brown eyes (bas...
 5.5.3BSC: Poission Approximation to Binomial Assume that we want to find the ...
 5.5.3CQQ: Using the same SAT questions described in Exercise, find the standa...
 5.5.3CRE: Tennis Challenge In the last U.S. Open tennis tournament, there wer...
 5.5.3RE: In Exercises, assume that 40% of the population has brown eyes (bas...
 5.5.4BSC: Poisson Approximation to Binomial Assume that we plan to play the T...
 5.5.4CQQ: If boys and girls are equally likely, groups of 400 births have a m...
 5.5.4CRE: Gender Gap In recent years, the discrepancy between incomes of wome...
 5.5.4RE: In Exercises, assume that 40% of the population has brown eyes (bas...
 5.5.5BSC: Aircraft Accidents. Assume that the Poisson distribution applies, a...
 5.5.5CRE: Random Digits The digits 0, 1, 2, 3, 4, 5, 6, 7, 8, and 9 are rando...
 5.5.6BSC: Aircraft Accidents. Assume that the Poisson distribution applies, a...
 5.5.6CRE: Investing in College Based on a USA Today poll, assume that 10% of ...
 5.5.7BSC: Aircraft Accidents. Assume that the Poisson distribution applies, a...
 5.5.7RE: Brand Recognition In a study of brand recognition of the Kindle eRe...
 5.5.8BSC: Aircraft Accidents. Assume that the Poisson distribution applies, a...
 5.5.8RE: Expected Value for Deal or No Deal In the television game show Deal...
 5.5.9BSC: Use the Poisson distribution to find the indicated probabilities.Ea...
 5.5.9CQQ: In Exercises, use the following: Five U.S. domestic flights are ran...
 5.5.9RE: Expected Value for a Magazine Sweepstakes Reader’s Digest ran a swe...
 5.5.10BSC: Use the Poisson distribution to find the indicated probabilities.Ea...
 5.5.10RE: Phone Calls In the month preceding the creation of this exercise, t...
 5.5.11BSC: Use the Poisson distribution to find the indicated probabilities.Ra...
 5.5.12BSC: Use the Poisson distribution to find the indicated probabilities.De...
 5.5.13BSC: Use the Poisson distribution to find the indicated probabilities.Wo...
 5.5.14BSC: Use the Poisson distribution to find the indicated probabilities.Di...
 5.5.15BSC: Use the Poisson distribution to find the indicated probabilities.Ch...
 5.5.17BB: Poisson Approximation to Binomial Distribution An experiment consis...
Solutions for Chapter 5.5: Elementary Statistics 12th Edition
Full solutions for Elementary Statistics  12th Edition
ISBN: 9780321836960
Solutions for Chapter 5.5
Get Full SolutionsSince 43 problems in chapter 5.5 have been answered, more than 159084 students have viewed full stepbystep solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 5.5 includes 43 full stepbystep solutions. 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.

2 k factorial experiment.
A full factorial experiment with k factors and all factors tested at only two levels (settings) each.

aerror (or arisk)
In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II error).

Additivity property of x 2
If two independent random variables X1 and X2 are distributed as chisquare with v1 and v2 degrees of freedom, respectively, Y = + X X 1 2 is a chisquare random variable with u = + v v 1 2 degrees of freedom. This generalizes to any number of independent chisquare random variables.

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.

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.

Categorical data
Data consisting of counts or observations that can be classiied into categories. The categories may be descriptive.

Central composite design (CCD)
A secondorder response surface design in k variables consisting of a twolevel factorial, 2k axial runs, and one or more center points. The twolevel 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 secondorder model.

Chance cause
The portion of the variability in a set of observations that is due to only random forces and which cannot be traced to speciic sources, such as operators, materials, or equipment. Also called a common cause.

Conditional probability density function
The probability density function of the conditional probability distribution of a continuous random variable.

Conditional variance.
The variance of the conditional probability distribution of a random variable.

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

Convolution
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.

Critical value(s)
The value of a statistic corresponding to a stated signiicance level as determined from the sampling distribution. For example, if PZ z PZ ( )( .) . ? =? = 0 025 . 1 96 0 025, then z0 025 . = 1 9. 6 is the critical value of z at the 0.025 level of signiicance. Crossed factors. Another name for factors that are arranged in a factorial experiment.

Decision interval
A parameter in a tabular CUSUM algorithm that is determined from a tradeoff between false alarms and the detection of assignable causes.

Estimate (or point estimate)
The numerical value of a point estimator.

Expected value
The expected value of a random variable X is its longterm 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.

Factorial experiment
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.

Gamma random variable
A random variable that generalizes an Erlang random variable to noninteger values of the parameter r

Geometric mean.
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 .

Hat matrix.
In multiple regression, the matrix H XXX X = ( ) ? ? 1 . This a projection matrix that maps the vector of observed response values into a vector of itted values by yˆ = = X X X X y Hy ( ) ? ? ?1 .