 5.2.1E: Defective DVDs From past experience, a company found that in carton...
 5.2.2E: Suit Sales The number of suits sold per day at a retail store is sh...
 5.2.3E: Number of Credit Cards A bank vice president feels that each saving...
 5.2.4E: Trivia Quiz The probabilities that a player will get 5 to 10 questi...
 5.2.5E: Cellular Phone Sales The probability that a cellular phone company ...
 5.2.6E: Traffic Accidents The county highway department recorded the follow...
 5.2.9E: Students Using the Math Lab The number of students using the Math L...
 5.2.10E: Pizza Deliveries A pizza shop owner determines the number of pizzas...
 5.2.12E: Job Bids A landscape contractor bids on jobs where he can make $300...
 5.2.13E: Rolling Dice If a person rolls doubles when she tosses two dice, sh...
 5.2.14E: Dice Game A person pays $2 to play a certain game by rolling a sing...
 5.2.15E: Lottery Prizes A lottery offers one $1000 prize, one $500 prize, an...
 5.2.16E: In Exercise 15. find the expectation if a person buys two tickets. ...
 5.2.17E: Winning the Lottery For a daily lottery, a person selects a threed...
 5.2.18E: Life Insurance A 35yearold woman purchases a $100,000 term life i...
 5.2.19E: Roulette A roulette wheel has 38 numbers, 1 through 36, 0, and 00. ...
 5.2.20EC: Rolling Dice Construct a probability distribution for the sum shown...
 5.2.21EC: Rolling a Die When one die is rolled, the expected value of the num...
 5.2.22EC: The formula for finding the variance for a probability distribution...
 5.2.23EC: Complete the following probability distribution if P(6) equals two...
 5.2.24EC: Rolling Two Dice Roll two dice 100 times and find the mean, varianc...
 5.2.25EC: Extracurricular Activities Conduct a survey of the number of extrac...
 5.2.26EC: Promotional Campaign In a recent promotional campaign, a company of...
Solutions for Chapter 5.2: Elementary Statistics: A Step By Step Approach 9th Edition
Full solutions for Elementary Statistics: A Step By Step Approach  9th Edition
ISBN: 9780073534985
Solutions for Chapter 5.2
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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).

Acceptance region
In hypothesis testing, a region in the sample space of the test statistic such that if the test statistic falls within it, the null hypothesis cannot be rejected. This terminology is used because rejection of H0 is always a strong conclusion and acceptance of H0 is generally a weak conclusion

Adjusted R 2
A variation of the R 2 statistic that compensates for the number of parameters in a regression model. Essentially, the adjustment is a penalty for increasing the number of parameters in the model. Alias. In a fractional factorial experiment when certain factor effects cannot be estimated uniquely, they are said to be aliased.

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.

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

Comparative experiment
An experiment in which the treatments (experimental conditions) that are to be studied are included in the experiment. The data from the experiment are used to evaluate the treatments.

Conditional probability
The probability of an event given that the random experiment produces an outcome in another event.

Conidence level
Another term for the conidence coeficient.

Control limits
See Control chart.

Correlation coeficient
A dimensionless measure of the linear association between two variables, usually lying in the interval from ?1 to +1, with zero indicating the absence of correlation (but not necessarily the independence of the two variables).

Critical region
In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.

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.

Dependent variable
The response variable in regression or a designed experiment.

Discrete distribution
A probability distribution for a discrete random variable

Error propagation
An analysis of how the variance of the random variable that represents that output of a system depends on the variances of the inputs. A formula exists when the output is a linear function of the inputs and the formula is simpliied if the inputs are assumed to be independent.

False alarm
A signal from a control chart when no assignable causes are present

Fisherâ€™s least signiicant difference (LSD) method
A series of pairwise hypothesis tests of treatment means in an experiment to determine which means differ.

Geometric random variable
A discrete random variable that is the number of Bernoulli trials until a success occurs.