 15.15.1: Numbers of rooms in top spas. A report of a readers poll in Cond Na...
 15.15.2: The effect of Animal Kingdom on the result. Refer to the previous e...
 15.15.3: Hypotheses and test statistic for top spas. Refer to Exercise 15.1....
 15.15.4: Effect of Animal Kingdom on the test statistic. Refer to Exercise 1...
 15.15.5: The Pvalue for top spas. Refer to Exercises 15.1 and 15.3 (pages 1...
 15.15.6: The effect of Animal Kingdom on the Pvalue. Refer to Exercises 15....
 15.15.7: Analyze as a twoway table. Analyze the exergaming data in Example ...
 15.15.8: Time spent studying. Students in a large firstyear college class we...
 15.15.9: Find the rank sum statistic. Refer to the previous exercise. Here a...
 15.15.10: State the hypotheses. Refer to the previous exercise. State appropr...
 15.15.11: Find the mean and standard deviation of the distribution of the sta...
 15.15.12: Find the Pvalue. Refer to Exercises 15.8 to 15.11. Find the Pvalu...
 15.15.13: Is civic engagement related to education? A Pew Internet Poll of ad...
 15.15.14: Do women talk more? Conventional wisdom suggests that women are mor...
 15.15.15: More data for women and men talking. The data in the previous exerc...
 15.15.16: Learning math through subliminal messages. A subliminal message is ...
 15.15.17: Storytelling and the use of language. A study of early childhood ed...
 15.15.18: Repeat the analysis for Story 2. Repeat the analysis of Exercise 15...
 15.15.19: Do the calculations by hand. Use the data in Exercise 15.17 for chi...
 15.15.20: Service and food provided by top 25 spas. The readers poll in Cond ...
 15.15.21: Scores for the next 25 spas. Refer to the previous exercise. Here a...
 15.15.22: Significance test for topranked spas. Refer to Exercise 15.20 (pag...
 15.15.23: Significance test for lowerranked spas. Refer to Exercise 15.21 (p...
 15.15.24: (b) Find the absolute values of the differences you found in part (...
 15.15.25: Find the Wilcoxon signed rank statistic. Using the work that you pe...
 15.15.26: State the hypotheses. Refer to Exercise 15.24. State the null hypot...
 15.15.27: Find the mean and the standard deviation. Refer to Exercise 15.24. ...
 15.15.28: Find the Pvalue. Refer to Exercises 15.24 to 15.27. Find the Pval...
 15.15.29: Read the output. The data in Exercise 15.24 are a subset of a large...
 15.15.30: Number of friends on Facebook. Facebook recently examined all activ...
 15.15.31: The matched pairs t test (Example 7.7, page 429) gives P 0.000015, ...
 15.15.32: Comparison of two energy drinks. Consider the following study to co...
 15.15.33: Comparison of two energy drinks with an additional subject. Refer t...
 15.15.34: A summer language institute for teachers. A matched pairs study of ...
 15.15.35: Radon detectors. How accurate are radon detectors of a type sold to...
 15.15.36: Radon detectors. How accurate are radon detectors of a type sold to...
 15.15.37: Number of Facebook friends. An experiment was run to examine the re...
 15.15.38: What are the hypotheses? Refer to the previous exercise. What are t...
 15.15.39: Read the output. Figure 15.11 gives the Minitab output for the anal...
 15.15.40: Do we experience emotions differently? In Exercise 12.37 (page 684)...
 15.15.41: Do isoflavones increase bone mineral density? In Exercise 12.45 (pa...
 15.15.42: Vitamins in bread. Does bread lose its vitamins when stored? Here a...
 15.15.43: Jumping and strong bones. In Exercise 12.47 (page 687) you studied ...
 15.15.44: Do poets die young? In Exercise 12.46 (page 686) you analyzed the a...
 15.15.45: Plants and hummingbirds. Different varieties of the tropical flower...
 15.15.46: Time spent studying. In Exercise 1.173 (page 50) you compared the t...
 15.15.47: Response times for telephone repair calls. A study examined the tim...
 15.15.48: Cooking vegetables in different pots. Does the vegetable dish vary ...
 15.15.49: Cooking meat and legumes in aluminum and clay pots. There appears t...
 15.15.50: Iron in food cooked in iron pots. The data show that food cooked in...
 15.15.51: Multiple comparisons for plants and hummingbirds. As in ANOVA, we o...
 15.15.52: Multiple comparisons for cooking pots. The previous exercise outlin...
Solutions for Chapter 15: Nonparametric Tests
Full solutions for Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card  8th Edition
ISBN: 9781464158933
Solutions for Chapter 15: Nonparametric Tests
Get Full SolutionsSince 52 problems in chapter 15: Nonparametric Tests have been answered, more than 31810 students have viewed full stepbystep solutions from this chapter. This expansive textbook survival guide covers the following chapters and their solutions. This textbook survival guide was created for the textbook: Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card, edition: 8. Introduction to the Practice of Statistics: w/CrunchIt/EESEE Access Card was written by and is associated to the ISBN: 9781464158933. Chapter 15: Nonparametric Tests includes 52 full stepbystep solutions.

Analytic study
A study in which a sample from a population is used to make inference to a future population. Stability needs to be assumed. See Enumerative study

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.

Binomial random variable
A discrete random variable that equals the number of successes in a ixed number of Bernoulli trials.

Block
In experimental design, a group of experimental units or material that is relatively homogeneous. The purpose of dividing experimental units into blocks is to produce an experimental design wherein variability within blocks is smaller than variability between blocks. This allows the factors of interest to be compared in an environment that has less variability than in an unblocked experiment.

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.

Conditional probability
The probability of an event given that the random experiment produces an outcome in another event.

Confounding
When a factorial experiment is run in blocks and the blocks are too small to contain a complete replicate of the experiment, one can run a fraction of the replicate in each block, but this results in losing information on some effects. These effects are linked with or confounded with the blocks. In general, when two factors are varied such that their individual effects cannot be determined separately, their effects are said to be confounded.

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

Cook’s distance
In regression, Cook’s distance is a measure of the inluence of each individual observation on the estimates of the regression model parameters. It expresses the distance that the vector of model parameter estimates with the ith observation removed lies from the vector of model parameter estimates based on all observations. Large values of Cook’s distance indicate that the observation is inluential.

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 .

Cumulative normal distribution function
The cumulative distribution of the standard normal distribution, often denoted as ?( ) x and tabulated in Appendix Table II.

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

Density function
Another name for a probability density function

Designed experiment
An experiment in which the tests are planned in advance and the plans usually incorporate statistical models. See Experiment

Discrete uniform random variable
A discrete random variable with a inite range and constant probability mass function.

Error propagation
An analysis of how the variance of the random variable that represents that output of a system depends on the variances of the inputs. A formula exists when the output is a linear function of the inputs and the formula is simpliied if the inputs are assumed to be independent.

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.

Factorial experiment
A type of experimental design in which every level of one factor is tested in combination with every level of another factor. In general, in a factorial experiment, all possible combinations of factor levels are tested.

Firstorder model
A model that contains only irstorder terms. For example, the irstorder response surface model in two variables is y xx = + ?? ? ? 0 11 2 2 + + . A irstorder model is also called a main effects model