 134.1: What is the purpose of the study?
 134.2: Are the samples independent or dependent?
 134.3: What are the hypotheses?
 134.4: What nonparametric test could be used to test the claim?
 134.5: What significance level would you use?
 134.6: What is your decision?
 134.7: What parametric test could you use?
 134.8: Would the results be the same?
 134.1: What is the parametric equivalent test for the Wilcoxon signedrank...
 134.2: For Exercises 2 and 3, find the sum of the signed ranks. Assume tha...
 134.3: For Exercises 2 and 3, find the sum of the signed ranks. Assume tha...
 134.4: For Exercises 4 through 8, use Table K to determine whether the nul...
 134.5: For Exercises 4 through 8, use Table K to determine whether the nul...
 134.6: For Exercises 4 through 8, use Table K to determine whether the nul...
 134.7: For Exercises 4 through 8, use Table K to determine whether the nul...
 134.8: For Exercises 4 through 8, use Table K to determine whether the nul...
 134.9: Drug Prices Eight drugs were selected, and the prices for the human...
 134.10: Salaries of Men and Women Workers In a corporation, female and male...
 134.11: Memorization Quiz Scores Nine students were selected to participate...
 134.12: Legal Costs for School Districts A sample of legal costs (in thousa...
 134.13: Drug Prices A researcher wishes to compare the prices for prescript...
Solutions for Chapter 134: Nonparametric Statistics
Full solutions for Elementary Statistics: A Step by Step Approach  7th Edition
ISBN: 9780073534978
Solutions for Chapter 134: Nonparametric Statistics
Get Full SolutionsThis textbook survival guide was created for the textbook: Elementary Statistics: A Step by Step Approach, edition: 7. This expansive textbook survival guide covers the following chapters and their solutions. Since 21 problems in chapter 134: Nonparametric Statistics have been answered, more than 6292 students have viewed full stepbystep solutions from this chapter. Chapter 134: Nonparametric Statistics includes 21 full stepbystep solutions. Elementary Statistics: A Step by Step Approach was written by Patricia and is associated to the ISBN: 9780073534978.

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

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

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.

Average run length, or ARL
The average number of samples taken in a process monitoring or inspection scheme until the scheme signals that the process is operating at a level different from the level in which it began.

Bayesâ€™ 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.

Bimodal distribution.
A distribution with two modes

Bivariate distribution
The joint probability distribution of two random variables.

C chart
An attribute control chart that plots the total number of defects per unit in a subgroup. Similar to a defectsperunit or U chart.

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.

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.

Covariance
A measure of association between two random variables obtained as the expected value of the product of the two random variables around their means; that is, Cov(X Y, ) [( )( )] =? ? E X Y ? ? X Y .

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

Decision interval
A parameter in a tabular CUSUM algorithm that is determined from a tradeoff between false alarms and the detection of assignable causes.

Density function
Another name for a probability density function

Dependent variable
The response variable in regression or a designed experiment.

Discrete distribution
A probability distribution for a discrete random variable

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

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

Harmonic mean
The harmonic mean of a set of data values is the reciprocal of the arithmetic mean of the reciprocals of the data values; that is, h n x i n i = ? ? ? ? ? = ? ? 1 1 1 1 g .
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