 132.1: What is the claim?
 132.2: What test would you use to test the claim? Why?
 132.3: What would the hypotheses be?
 132.4: Select a value for a and find the corresponding critical value
 132.5: What is the test value?
 132.6: What is your decision?
 132.7: Summarize the results.
 132.8: Could a parametric test be used?
 132.1: Why is the sign test the simplest nonparametric test to use?
 132.2: What population parameter can be tested with the sign test?
 132.3: In the sign test, what is used as the test value when n 26?
 132.4: When n 26, what is used in place of Table J for the sign test?
 132.5: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.6: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.7: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.8: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.9: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.10: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.11: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.12: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.13: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.14: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.15: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.16: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.17: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.18: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.19: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.20: For Exercises 5 through 20, perform these steps. a. State the hypot...
 132.21: For Exercises 21 through 25, find the confidence interval of the me...
 132.22: For Exercises 21 through 25, find the confidence interval of the me...
 132.23: For Exercises 21 through 25, find the confidence interval of the me...
 132.24: For Exercises 21 through 25, find the confidence interval of the me...
 132.25: For Exercises 21 through 25, find the confidence interval of the me...
Solutions for Chapter 132: Nonparametric Statistics
Full solutions for Elementary Statistics: A Step by Step Approach  7th Edition
ISBN: 9780073534978
Solutions for Chapter 132: Nonparametric Statistics
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aerror (or arisk)
In hypothesis testing, an error incurred by failing to reject a null hypothesis when it is actually false (also called a type II error).

Analysis of variance (ANOVA)
A method of decomposing the total variability in a set of observations, as measured by the sum of the squares of these observations from their average, into component sums of squares that are associated with speciic deined sources of variation

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.

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).

Causeandeffect diagram
A chart used to organize the various potential causes of a problem. Also called a ishbone diagram.

Completely randomized design (or experiment)
A type of experimental design in which the treatments or design factors are assigned to the experimental units in a random manner. In designed experiments, a completely randomized design results from running all of the treatment combinations in random order.

Components of variance
The individual components of the total variance that are attributable to speciic sources. This usually refers to the individual variance components arising from a random or mixed model analysis of variance.

Conditional probability distribution
The distribution of a random variable given that the random experiment produces an outcome in an event. The given event might specify values for one or more other random variables

Conidence level
Another term for the conidence coeficient.

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 .

Covariance matrix
A square matrix that contains the variances and covariances among a set of random variables, say, X1 , X X 2 k , , … . The main diagonal elements of the matrix are the variances of the random variables and the offdiagonal elements are the covariances between Xi and Xj . Also called the variancecovariance matrix. When the random variables are standardized to have unit variances, the covariance matrix becomes the correlation matrix.

Crossed factors
Another name for factors that are arranged in a factorial experiment.

Cumulative sum control chart (CUSUM)
A control chart in which the point plotted at time t is the sum of the measured deviations from target for all statistics up to time t

Dispersion
The amount of variability exhibited by data

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

Error of estimation
The difference between an estimated value and the true value.

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.

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