 Chapter 12.4.1AYU: Intervals constructed about the predicted value of y, at a given le...
 Chapter 12.4.1CT: A pit boss is concerned that a pair of dice being used in a craps g...
 Chapter 12.4.1RE: Roulette Wheel A pit boss suspects that a roulette wheel is out of ...
 Chapter 12.4.2AYU: Intervals constructed about the predicted value of y, at a given le...
 Chapter 12.4.2CT: A researcher wanted to determine if the distribution of educational...
 Chapter 12.4.2RE: World Series Are the teams that play in the World Series evenly mat...
 Chapter 12.4.3AYU: use the results of Problems.Using the sample data from Section(a)Pr...
 Chapter 12.4.3CT: In a poll conducted by Harris Poll, a random sample of adult Americ...
 Chapter 12.4.3RE: Titanic With 20% of men, 74% of women, and 52% of children survivin...
 Chapter 12.4.4AYU: Using the sample data from Section(a) Predict the mean value of y i...
 Chapter 12.4.4CT: The General Social Survey regularly asks individuals to disclose th...
 Chapter 12.4.4RE: Premature Birth and Education Does the length of term of pregnancy ...
 Chapter 12.4.5AYU: Using the sample data from Section(a) Predict the mean value of y i...
 Chapter 12.4.5CT: Many municipalities are passing legislation that forbids smoking in...
 Chapter 12.4.5RE: Roosevelt versus Landon One of the most famous presidential electio...
 Chapter 12.4.6AYU: Using the sample data from Section(a) Predict the mean value of y i...
 Chapter 12.4.6CT: State the requirements to perform inference on a simple leastsquar...
 Chapter 12.4.6RE: What is the simple leastsquares regression model? What are the req...
 Chapter 12.4.7AYU: An Unhealthy CommuteUse the results of Section to answer the follow...
 Chapter 12.4.7CT: Crickets make a chirping noise by sliding their wings rapidly over ...
 Chapter 12.4.7RE: Seat Choice and GPAA biology professor wants to investigate the rel...
 Chapter 12.4.8AYU: Credit ScoresUse the results of Section to answer the following que...
 Chapter 12.4.8CT: The following data represent the height (inches) of boys between th...
 Chapter 12.4.8RE: ApartmentsThe following data represent the square footage and rents...
 Chapter 12.4.9AYU: Height versus Head Circumference Use the results of Section to answ...
 Chapter 12.4.9CT: A researcher believes that as age increases the grip strength (poun...
 Chapter 12.4.10AYU: Bone LengthUse the results of Section to answer the following quest...
 Chapter 12.4.11AYU: Concrete Use the results of Section to answer the following questio...
 Chapter 12.4.12AYU: Tar and NicotineUse the results of Section to answer the following ...
 Chapter 12.4.13AYU: United Technologies versus the S&P 500 Use the results of Section t...
 Chapter 12.4.14AYU: American Black BearsUse the results of Section to answer the follow...
 Chapter 12.4.15AYU: CEO Performance Use the results of Section to answer the following:...
 Chapter 12.4.16AYU: Calories versus Sugar Use the results of Section to answer the foll...
 Chapter 12.4.17AYU: Putting It Together: 3D Television Prices One factor that influence...
Solutions for Chapter Chapter 12.4: Fundamentals of Statistics 4th Edition
Full solutions for Fundamentals of Statistics  4th Edition
ISBN: 9780321838704
Solutions for Chapter Chapter 12.4
Get Full SolutionsSince 34 problems in chapter Chapter 12.4 have been answered, more than 305270 students have viewed full stepbystep solutions from this chapter. Fundamentals of Statistics was written by and is associated to the ISBN: 9780321838704. Chapter Chapter 12.4 includes 34 full stepbystep solutions. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Fundamentals of Statistics, edition: 4.

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.

Asymptotic relative eficiency (ARE)
Used to compare hypothesis tests. The ARE of one test relative to another is the limiting ratio of the sample sizes necessary to obtain identical error probabilities for the two procedures.

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

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

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

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.

Cumulative normal distribution function
The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.

Curvilinear regression
An expression sometimes used for nonlinear regression models or polynomial regression models.

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

Discrete distribution
A probability distribution for a discrete random variable

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

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.

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.

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.

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.

Fraction defective control chart
See P chart

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.