 4.4.1E: Twenty airconditioning units have been brought in for service. Twe...
 4.4.2E: There are 30 restaurants in a certain town. Assume that four of the...
 4.4.3E: The probability that a computer running a certain operating system ...
 4.4.4E: A traffic light at a certain intersection is green 50% of the time,...
 4.4.5E: Refer to Exercise 4. Let Y denote the number of days up to and incl...
 4.4.6E: Refer to Exercise 4. What is the probability that in a sequence of ...
 4.4.7E: if X~Geom(p),what is the most probable value of X?i. 0_____________...
 4.4.8E: A process that fills packages is stopped whenever a package is dete...
 4.4.9E: A system is tested for faults once per hour. If there is no fault, ...
 4.4.10E: A computer program has a bug that causes it to fail once in every t...
 4.4.11E: In a lot of 10 microcircuits, 3 are defective. Four microcircuits a...
 4.4.12E: A lot of parts contains 500 items, 100 of which are defective. Supp...
 4.4.13E: Ten items are to be sampled from a lot of 60. If morethan one is el...
 4.4.14E: Of customers ordering a certain type of personal computer, 20% orde...
 4.4.15E: At a certain fastfood restaurant, 25% of drink orders are for a sm...
 4.4.16E: A thermocouple placed in a certain medium produces readings within ...
 4.4.17E: Let X ~ Geom(p), let n be a nonnegative integer, and let Y ~ Bin(n...
 4.4.18E: use the result of 17 and table A.1 to find P(X=10)where X~Geom(0.3).
Solutions for Chapter 4.4: Statistics for Engineers and Scientists 4th Edition
Full solutions for Statistics for Engineers and Scientists  4th Edition
ISBN: 9780073401331
Solutions for Chapter 4.4
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`error (or `risk)
In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).

Addition rule
A formula used to determine the probability of the union of two (or more) events from the probabilities of the events and their intersection(s).

Alternative hypothesis
In statistical hypothesis testing, this is a hypothesis other than the one that is being tested. The alternative hypothesis contains feasible conditions, whereas the null hypothesis speciies conditions that are under test

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.

Bimodal distribution.
A distribution with two modes

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

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

Confounding
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.

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.

Crossed factors
Another name for factors that are arranged in a factorial experiment.

Deming
W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

Dispersion
The amount of variability exhibited by data

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

Estimator (or point estimator)
A procedure for producing an estimate of a parameter of interest. An estimator is usually a function of only sample data values, and when these data values are available, it results in an estimate of the parameter of interest.

Exhaustive
A property of a collection of events that indicates that their union equals the sample space.

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

Fractional factorial experiment
A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.

Generating function
A function that is used to determine properties of the probability distribution of a random variable. See Momentgenerating function

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.