 12.1.1: Statistical Literacy To apply the sign test, do you need independen...
 12.1.2: Statistical Literacy For the sign test of matched pairs, do pairs f...
 12.1.3: Economic Growth: Asia Asian economies impact some of the worlds lar...
 12.1.4: Debt: Developing Countries Borrowing money may be necessary for bus...
 12.1.5: Education: Exams A high school science teacher decided to give a se...
 12.1.6: Grain Yields: Feeding the World With an everincreasing world popul...
 12.1.7: Identical Twins: Reading Skills To compare two elementary schools r...
 12.1.8: Incomes: Electricians and Carpenters How do the average weekly inco...
 12.1.9: Quitting Smoking: Hypnosis One program to help people stop smoking ...
 12.1.10: Incomes: Lawyers and Architects How do the average weekly incomes o...
 12.1.11: High School Dropouts: Male versus Female Is the high school dropout...
 12.1.12: Focus Problem: Meteorology The Focus the beginning of this chapter ...
Solutions for Chapter 12.1: NONPARAMETRIC STATISTICS
Full solutions for Understandable Statistics  9th Edition
ISBN: 9780618949922
Solutions for Chapter 12.1: NONPARAMETRIC STATISTICS
Get Full SolutionsThis textbook survival guide was created for the textbook: Understandable Statistics, edition: 9. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 12.1: NONPARAMETRIC STATISTICS includes 12 full stepbystep solutions. Understandable Statistics was written by and is associated to the ISBN: 9780618949922. Since 12 problems in chapter 12.1: NONPARAMETRIC STATISTICS have been answered, more than 35307 students have viewed full stepbystep solutions from this chapter.

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

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.

Attribute control chart
Any control chart for a discrete random variable. See Variables control chart.

Bernoulli trials
Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.

Causal variable
When y fx = ( ) and y is considered to be caused by x, x is sometimes called a causal variable

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.

Combination.
A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.

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 mean
The mean of the conditional probability distribution of a random variable.

Continuous distribution
A probability distribution for a continuous random variable.

Distribution function
Another name for a cumulative distribution function.

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

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.

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.

F distribution.
The distribution of the random variable deined as the ratio of two independent chisquare random variables, each divided by its number of degrees of freedom.

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.

Forward selection
A method of variable selection in regression, where variables are inserted one at a time into the model until no other variables that contribute signiicantly to the model can be found.

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 .