 136.1: What question are you trying to answer?
 136.2: What type of nonparametric analysis could be used to answer the que...
 136.3: What would be the corresponding parametric test that could be used?
 136.4: Which test do you think would be better?
 136.5: Perform both tests and write a short statement comparing the results
 136.1: For Exercises 1 through 4, find the critical value from Table L for...
 136.2: For Exercises 1 through 4, find the critical value from Table L for...
 136.3: For Exercises 1 through 4, find the critical value from Table L for...
 136.4: For Exercises 1 through 4, find the critical value from Table L for...
 136.5: For Exercises 5 through 14, perform these steps. a. Find the Spearm...
 136.6: For Exercises 5 through 14, perform these steps. a. Find the Spearm...
 136.7: For Exercises 5 through 14, perform these steps. a. Find the Spearm...
 136.8: For Exercises 5 through 14, perform these steps. a. Find the Spearm...
 136.9: For Exercises 5 through 14, perform these steps. a. Find the Spearm...
 136.10: For Exercises 5 through 14, perform these steps. a. Find the Spearm...
 136.11: For Exercises 5 through 14, perform these steps. a. Find the Spearm...
 136.12: For Exercises 5 through 14, perform these steps. a. Find the Spearm...
 136.13: For Exercises 5 through 14, perform these steps. a. Find the Spearm...
 136.14: For Exercises 5 through 14, perform these steps. a. Find the Spearm...
 136.15: A school dentist wanted to test the claim, at a 0.05, that the numb...
 136.16: Daily Lottery Numbers Listed below are the daily numbers (daytime d...
 136.17: Lottery Numbers The winning numbers for the Pennsylvania State Lott...
 136.18: True/False Test Answers An irate student believes that the answers ...
 136.19: Concert Seating As students, faculty, friends, and family arrived f...
 136.20: Twenty shoppers are in a checkout line at a grocery store. At a 0.0...
 136.21: Employee Absences A supervisor records the number of employees abse...
 136.22: Skiing Conditions A ski lodge manager observes the weather for the ...
 136.23: Tossing a Coin Toss a coin 30 times and record the outcomes (H or T...
 136.24: For Exercises 24 through 28, find the critical r value for each (as...
 136.25: For Exercises 24 through 28, find the critical r value for each (as...
 136.26: For Exercises 24 through 28, find the critical r value for each (as...
 136.27: For Exercises 24 through 28, find the critical r value for each (as...
 136.28: For Exercises 24 through 28, find the critical r value for each (as...
Solutions for Chapter 136: Nonparametric Statistics
Full solutions for Elementary Statistics: A Step by Step Approach  7th Edition
ISBN: 9780073534978
Solutions for Chapter 136: Nonparametric Statistics
Get Full SolutionsElementary Statistics: A Step by Step Approach was written by and is associated to the ISBN: 9780073534978. Since 33 problems in chapter 136: Nonparametric Statistics have been answered, more than 13463 students have viewed full stepbystep solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. Chapter 136: Nonparametric Statistics includes 33 full stepbystep solutions. This textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach, edition: 7.

Average
See Arithmetic mean.

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.

Central limit theorem
The simplest form of the central limit theorem states that the sum of n independently distributed random variables will tend to be normally distributed as n becomes large. It is a necessary and suficient condition that none of the variances of the individual random variables are large in comparison to their sum. There are more general forms of the central theorem that allow ininite variances and correlated random variables, and there is a multivariate version of the theorem.

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.

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

Control chart
A graphical display used to monitor a process. It usually consists of a horizontal center line corresponding to the incontrol value of the parameter that is being monitored and lower and upper control limits. The control limits are determined by statistical criteria and are not arbitrary, nor are they related to speciication limits. If sample points fall within the control limits, the process is said to be incontrol, or free from assignable causes. Points beyond the control limits indicate an outofcontrol process; that is, assignable causes are likely present. This signals the need to ind and remove the assignable causes.

Correlation
In the most general usage, a measure of the interdependence among data. The concept may include more than two variables. The term is most commonly used in a narrow sense to express the relationship between quantitative variables or ranks.

Correlation matrix
A square matrix that contains the correlations among a set of random variables, say, XX X 1 2 k , ,…, . The main diagonal elements of the matrix are unity and the offdiagonal elements rij are the correlations between Xi and Xj .

Counting techniques
Formulas used to determine the number of elements in sample spaces and events.

Cumulative distribution function
For a random variable X, the function of X deined as PX x ( ) ? that is used to specify the probability distribution.

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.

Dispersion
The amount of variability exhibited by data

Error variance
The variance of an error term or component in a model.

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.

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.

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.

Fraction defective control chart
See P chart

Gaussian distribution
Another name for the normal distribution, based on the strong connection of Karl F. Gauss to the normal distribution; often used in physics and electrical engineering applications

Generating function
A function that is used to determine properties of the probability distribution of a random variable. See Momentgenerating function