 26.1: 1. Which test? For each of the following situations, statewhether y...
 26.2: 2. Which test again? For each of the following situations,state whe...
 26.3: 3. Dice. After getting trounced by your little brother in achildren...
 26.4: 4. M&Ms. As noted in an earlier chapter, the MasterfoodsCompany say...
 26.5: 5. Nuts. A company says its premium mixture of nutscontains 10% Bra...
 26.6: 6. Mileage. A salesman who is on the road visiting clients thinks t...
 26.7: 7. NYPD and race. Census data for New York City indicatethat 29.2% ...
 26.8: 8. Violence against women 2005. In its study When Men Murder Women,...
 26.9: 9. Fruit flies. Offspring of certain fruit flies may have yellowor ...
 26.10: 10. Pi. Many people know the mathematicalconstant is approximately3...
 26.11: 11. Hurricane frequencies. The National Hurricane Centerprovides da...
 26.12: 12. Lottery numbers. The fairness of the South Africanlottery was r...
 26.13: 13. Childbirth, part 1. There is some concern that if awoman has an...
 26.14: 14. Does your doctor know? A survey7 of articles fromthe New Englan...
 26.15: 15. Childbirth, part 2. In Exercise 13, the table shows resultsof a...
 26.16: 16. Does your doctor know? (part 2). The table in Exercise14 shows ...
 26.17: 17. Childbirth, part 3. In Exercises 13 and 15, weve begunto examin...
 26.18: 18. Does your doctor know? (part 3). In Exercises 14 and16, weve be...
 26.19: 19. Childbirth, part 4. In Exercises 13, 15, and 17, wevetested a h...
 26.20: 20. Does your doctor know? (part 4). In Exercises 14, 16,and 18, we...
 26.21: 21. Childbirth, part 5. In Exercises 13, 15, 17, and 19,weve looked...
 26.22: 22. Does your doctor know? (part 5). In Exercises 14, 16,18, and 20...
 26.23: 23. Titanic. Here is a table we first saw in Chapter 3 showingwho s...
 26.24: 24. NYPD and sex discrimination. The table belowshows the rank atta...
 26.25: Titanic again. Examine and comment on this table ofthe standardized...
 26.26: 26. NYPD again. Examine and comment on this table ofthe standardize...
 26.27: 27. Cranberry juice. Its common folk wisdom that drinkingcranberry ...
 26.28: 28. Cars. A random survey of autos parked in the studentlot and the...
 26.29: 29. Montana. A poll conducted by the University of Montanaclassifie...
 26.30: 30. Fish diet. Medical researchers followed 6272 Swedishmen for 30 ...
 26.31: 31. Montana revisited. The poll described in Exercise 29also invest...
 26.32: 32. Working parents. In July 1991 and again in April2001, the Gallu...
 26.33: 33. Grades. Two different professors teach an introductoryStatistic...
 26.34: 34. Full moon. Some people believe that a full moon elicitsunusual ...
 26.35: 35. Grades again. In some situations where the expectedcell counts ...
 26.36: 36. Full moon, next phase. In Exercise 34 you found thatthe expecte...
 26.37: 37. Racial steering. A subtle form of racial discriminationin housi...
 26.38: 38. Titanic, redux. Newspaper headlines at the time, andtraditional...
 26.39: 39. Steering revisited. You could have checked the datain Exercise ...
 26.40: 40. Survival on the Titanic, one more time. In Exercise38 you could...
 26.41: 41. Pregnancies. Most pregnancies result in live births, butsome en...
 26.42: 42. Education by age. Use the survey results in the tableto investi...
Solutions for Chapter 26: Comparing Counts
Full solutions for Stats: Modeling The World  3rd Edition
ISBN: 9780131359581
Solutions for Chapter 26: Comparing Counts
Get Full SolutionsThis expansive textbook survival guide covers the following chapters and their solutions. Since 42 problems in chapter 26: Comparing Counts have been answered, more than 38863 students have viewed full stepbystep solutions from this chapter. Chapter 26: Comparing Counts includes 42 full stepbystep solutions. This textbook survival guide was created for the textbook: Stats: Modeling The World , edition: 3. Stats: Modeling The World was written by and is associated to the ISBN: 9780131359581.

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

`error (or `risk)
In hypothesis testing, an error incurred by rejecting a null hypothesis when it is actually true (also called a type I error).

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).

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

Bayes’ theorem
An equation for a conditional probability such as PA B (  ) in terms of the reverse conditional probability PB A (  ).

Bias
An effect that systematically distorts a statistical result or estimate, preventing it from representing the true quantity of interest.

Bimodal distribution.
A distribution with two modes

Bivariate distribution
The joint probability distribution of two random variables.

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.

Continuity correction.
A correction factor used to improve the approximation to binomial probabilities from a normal distribution.

Critical region
In hypothesis testing, this is the portion of the sample space of a test statistic that will lead to rejection of the null hypothesis.

Curvilinear regression
An expression sometimes used for nonlinear regression models or polynomial regression models.

Deming
W. Edwards Deming (1900–1993) was a leader in the use of statistical quality control.

Dispersion
The amount of variability exhibited by data

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

Fractional factorial experiment
A type of factorial experiment in which not all possible treatment combinations are run. This is usually done to reduce the size of an experiment with several factors.

Generator
Effects in a fractional factorial experiment that are used to construct the experimental tests used in the experiment. The generators also deine the aliases.