 14.2.1: ?Intervals constructed about the predicted value of y, at a given l...
 14.2.2: ?Intervals constructed about the predicted value of y, at a given l...
 14.2.3: ?In 3–6, use the results of 5–8 in Section 14.13. Using the sample ...
 14.2.4: ?In 3–6, use the results of 5–8 in Section 14.14. Using the sample ...
 14.2.5: ?In 3–6, use the results of 5–8 in Section 14.15. Using the sample ...
 14.2.6: ?In 3–6, use the results of 5–8 in Section 14.16. Using the sample ...
 14.2.7: ?An Unhealthy Commute Use the results of from Section 14.1 to answe...
 14.2.8: ?Credit Scores Use the results of from Section 14.1 to answer the f...
 14.2.9: ?Height versus Head Circumference Use the results of from Section 1...
 14.2.10: ?Hurricanes Use the results of in Section 14.1 to answer the follow...
 14.2.11: ?Concrete Use the results of from Section 14.1 to answer the follow...
 14.2.12: ?Tar and Nicotine Use the results of in Section 14.1 to answer the ...
 14.2.13: ?Invest in Education Use the results of in Section 14.1 to answer t...
 14.2.14: ?American Black Bears Use the results of from Section 14.1 to answe...
 14.2.15: ?CEO Performance Use the results of from Section 14.1 to answer the...
 14.2.16: ?Bear Markets Use the results of from Section 14.1 to answer the fo...
 14.2.17: ?Putting It Together: Predicting Intelligence Can a photograph of a...
Solutions for Chapter 14.2: Confidence and Prediction Intervals
Full solutions for Statistics: Informed Decisions Using Data  5th Edition
ISBN: 9780134133539
Solutions for Chapter 14.2: Confidence and Prediction Intervals
Get Full SolutionsSummary of Chapter 14.2: Confidence and Prediction Intervals
Construct confidence intervals for a mean response. Construct prediction intervals for an individual response.
Since 17 problems in chapter 14.2: Confidence and Prediction Intervals have been answered, more than 27599 students have viewed full stepbystep solutions from this chapter. Statistics: Informed Decisions Using Data was written by and is associated to the ISBN: 9780134133539. Chapter 14.2: Confidence and Prediction Intervals includes 17 full stepbystep solutions. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Statistics: Informed Decisions Using Data, edition: 5.

`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).

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.

Bayes’ estimator
An estimator for a parameter obtained from a Bayesian method that uses a prior distribution for the parameter along with the conditional distribution of the data given the parameter to obtain the posterior distribution of the parameter. The estimator is obtained from the posterior distribution.

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.

Center line
A horizontal line on a control chart at the value that estimates the mean of the statistic plotted on the chart. See Control chart.

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.

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.

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 mass function
The probability mass function of the conditional probability distribution of a discrete random variable.

Consistent estimator
An estimator that converges in probability to the true value of the estimated parameter as the sample size increases.

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

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.

Defect
Used in statistical quality control, a defect is a particular type of nonconformance to speciications or requirements. Sometimes defects are classiied into types, such as appearance defects and functional defects.

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).

Empirical model
A model to relate a response to one or more regressors or factors that is developed from data obtained from the system.

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

Experiment
A series of tests in which changes are made to the system under study

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.