 15.15.1.1: Restaurant Service Times (a) Construct the empirical cumulative dis...
 15.15.1.2: Paving Slab Weights (a) Construct the empirical cumulative distribu...
 15.15.1.3: Spray Painting Procedure Construct the empirical cumulative distrib...
 15.15.1.4: Plastic Panel Bending Capabilities Construct the empirical cumulati...
 15.15.1.5: Suppose that the data set in DS 15.1.1 consists of values that can ...
 15.15.1.6: Repeat 15.1.5 using the data set in DS 15.1.2 and for the null hypo...
 15.15.1.7: Production Line Assembly Methods Use the sign test and the signed r...
 15.15.1.8: Red Blood Cell Adherence to Endothelial Cells Use the sign test and...
 15.15.1.9: Calculus Teaching Methods Use the sign test and the signed rank tes...
 15.15.1.10: Radioactive Carbon Dating Use the sign test and the signed rank tes...
 15.15.1.11: Golf Ball Design Use the sign test and the signed rank test to anal...
 15.15.1.12: Carbon Footprints Analyze the data in DS 6.7.15, which contain esti...
 15.15.1.13: Data Warehouse Design Powerconsumptionrepresentsalargeproportionofa...
 15.15.1.14: Customer Churn Customer churn is a term used for the attrition of a...
 15.15.1.15: Mining Mill Operations DS 6.7.18 contains daily data for the mill o...
 15.15.2.1: Restaurant Service Times Recall that DS 6.1.4 shows the service tim...
 15.15.2.2: Paving Slab Weights Recall that DS 6.1.7 shows the weights of a sam...
 15.15.2.3: HeelStrike Force on a Treadmill DS 9.3.3 contains observations of ...
 15.15.2.4: Use the rank sum test procedure to analyze the two samples in DS 15...
 15.15.2.5: Repeat 15.2.4 using the data set in DS 15.2.2.
 15.15.2.6: Use the rank sum test to analyze the data set in Figure 9.20 concer...
 15.15.2.7: Spray Painting Procedure Recall that DS 6.1.8 contains a sample of ...
 15.15.2.8: Bleaching Agents RecallthatDS9.3.4containstheresultsofanexperiment ...
 15.15.2.9: Clinical Trial Use the rank sum test to analyze the clinical trial ...
 15.15.2.10: Carbon Footprints Use the methods discussed in this chapter to anal...
 15.15.2.11: Green Management A company introduces green management techniques t...
 15.15.2.12: Data Warehouse Design Power consumption represents a large proporti...
 15.15.2.13: Natural Gas Consumption DS 9.7.18 contains data on the total daily ...
 15.15.3.1: Use the KruskalWallis test procedure to analyze the data in DS 11....
 15.15.3.2: Use the KruskalWallis test procedure to analyze the data in DS 11....
 15.15.3.3: Infrared Radiation Readings The data set in DS 11.1.3 concerns the ...
 15.15.3.4: Keyboard Layout Designs DS 11.1.4 contains the times taken to perfo...
 15.15.3.5: Computer Assembly Methods DS 11.1.6 contains the assembly times of ...
 15.15.3.6: Use the Friedman test procedure to analyze the data in DS 11.2.1. (...
 15.15.3.7: Use the Friedman test procedure to analyze the data in DS 11.2.2. (...
 15.15.3.8: Calciner Comparisons The data set in DS 11.2.3 concerns the brightn...
 15.15.3.9: Radar Detection of Airborne Objects DS 11.2.4 contains distances at...
 15.15.3.10: Production Line Assembly Methods The data set in DS 11.2.6 concerns...
 15.15.3.11: Realtor Commissions DS 11.2.7 contains the commissions obtained by ...
 15.15.3.12: Cleanliness Scores for Detergent Comparisons The data set in DS 11....
 15.15.3.13: Durations of Investigatory Surgical Procedures Use the appropriate ...
 15.15.3.14: E. Coli Colonies in Riverwater Use the appropriate nonparametric me...
 15.15.3.15: Groundwater Pollution Levels Use the appropriate nonparametric meth...
 15.15.3.16: Volatile Organic Carbon Emissions Volatile organic carbon emissions...
 15.15.5.1: Osteoporosis Patient Heights (a) Construct the empirical cumulative...
 15.15.5.2: Bamboo Cultivation Construct the empirical cumulative distribution ...
 15.15.5.3: Tire Tread Wear Use the sign test and the signed rank test to analy...
 15.15.5.4: Video Display Designs Use the sign test and the signed rank test to...
 15.15.5.5: Consumer Complaints Division Reorganization Recall that DS 9.7.4 co...
 15.15.5.6: Bamboo Cultivation A researcher compares the bamboo shoot heights i...
 15.15.5.7: Use the rank sum test to analyze the data set in Figure 9.24 concer...
 15.15.5.8: Biaxial Nanowire Tests DS 11.5.1 contains Youngs modulus measuremen...
 15.15.5.9: Car Gas Efciencies The data set in DS 11.5.2 concerns the gas milea...
 15.15.5.10: Temperature Effect on Cement Curing Use the Friedman test procedure...
 15.15.5.11: Fertilizer Comparisons DS 11.5.4 contains the results of an experim...
 15.15.5.12: Red Blood Cell Adhesion to Endothelial Cells The data set in DS 11....
 15.15.5.13: Soil Compressibility Tests Recall the data set of soil compressibil...
 15.15.5.14: Ocular Motor Measurements DS 9.7.5 contains the data from an experi...
 15.15.5.15: Engine Oil Viscosity Oil viscosity values obtained from two engines...
 15.15.5.16: Insertion Gains of Hearing Aids Data collected on the insertion gai...
 15.15.5.17: Air Resistance Drag for Road Vehicles Data from wind tunnel tests p...
 15.15.5.18: Leather Shrinkage Measurements The shrinkage measurements of leathe...
 15.15.5.19: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.20: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.21: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.22: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.23: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.24: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.25: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.26: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.27: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.28: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.29: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.30: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.31: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.32: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.33: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.34: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.35: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.36: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.37: Use the appropriate nonparametric methodologies from this chapter t...
 15.15.5.38: Customer Churn Customer churn is a term used for the attrition of a...
 15.15.5.39: Mercury Levels in Coal DS 6.7.19 shows the mercury levels of coal s...
Solutions for Chapter 15: Nonparametric Statistical Analysis
Full solutions for Probability and Statistics for Engineers and Scientists  4th Edition
ISBN: 9781111827045
Solutions for Chapter 15: Nonparametric Statistical Analysis
Get Full SolutionsChapter 15: Nonparametric Statistical Analysis includes 83 full stepbystep solutions. Probability and Statistics for Engineers and Scientists was written by and is associated to the ISBN: 9781111827045. This expansive textbook survival guide covers the following chapters and their solutions. Since 83 problems in chapter 15: Nonparametric Statistical Analysis have been answered, more than 11778 students have viewed full stepbystep solutions from this chapter. This textbook survival guide was created for the textbook: Probability and Statistics for Engineers and Scientists, edition: 4.

2 k p  factorial experiment
A fractional factorial experiment with k factors tested in a 2 ? p fraction with all factors tested at only two levels (settings) each

Alternative hypothesis
In statistical hypothesis testing, this is a hypothesis other than the one that is being tested. The alternative hypothesis contains feasible conditions, whereas the null hypothesis speciies conditions that are under test

Arithmetic mean
The arithmetic mean of a set of numbers x1 , x2 ,…, xn is their sum divided by the number of observations, or ( / )1 1 n xi t n ? = . The arithmetic mean is usually denoted by x , and is often called the average

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.

Axioms of probability
A set of rules that probabilities deined on a sample space must follow. See Probability

Backward elimination
A method of variable selection in regression that begins with all of the candidate regressor variables in the model and eliminates the insigniicant regressors one at a time until only signiicant regressors remain

Biased estimator
Unbiased estimator.

Box plot (or box and whisker plot)
A graphical display of data in which the box contains the middle 50% of the data (the interquartile range) with the median dividing it, and the whiskers extend to the smallest and largest values (or some deined lower and upper limits).

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.

Continuous uniform random variable
A continuous random variable with range of a inite interval and a constant probability density function.

Contour plot
A twodimensional graphic used for a bivariate probability density function that displays curves for which the probability density function is constant.

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.

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

Erlang random variable
A continuous random variable that is the sum of a ixed number of independent, exponential random variables.

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.

Frequency distribution
An arrangement of the frequencies of observations in a sample or population according to the values that the observations take on

Gamma random variable
A random variable that generalizes an Erlang random variable to noninteger values of the parameter r

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