- 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 ever-increasing 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
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.
Sequences of independent trials with only two outcomes, generally called “success” and “failure,” in which the probability of success remains constant.
When y fx = ( ) and y is considered to be caused by x, x is sometimes called a causal variable
Central composite design (CCD)
A second-order response surface design in k variables consisting of a two-level factorial, 2k axial runs, and one or more center points. The two-level 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 second-order model.
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.
A subset selected without replacement from a set used to determine the number of outcomes in events and sample spaces.
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.
The mean of the conditional probability distribution of a random variable.
A probability distribution for a continuous random variable.
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.
The expected value of a random variable X is its long-term 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.
The distribution of the random variable deined as the ratio of two independent chi-square 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.
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.
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 .
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 .