Chapter 9: Q19E (page 542)
Refer to Exercises 9.17 and 9.18. Complete the following ANOVA table for each of the two dot plots:
The F-ratio for dot plot #1 is 37.5 and for dot plot #2 is 5.21
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Identifying the type of experiment. Brief descriptions of a number of experiments are given next. Determine whether each is observational or designed and explain your reasoning.
a. An economist obtains the unemployment rate and gross state product for a sample of states over the past 10 years, with the objective of examining the relationship between the unemployment rate and the gross state product by census region.
b. A manager in a paper production facility installs one of three incentive programs in each of nine plants to determine the effect of each program on productivity.
c. A marketer of personal computers runs ads in each of four national publications for one quarter and keeps track of the number of sales that are attributable to each publication’s ad.
d. An electric utility engages a consultant to monitor the discharge from its smokestack on a monthly basis over a 1-year period to relate the level of sulfur dioxide in the discharge to the load on the facility’s generators.
e. Intrastate trucking rates are compared before and after governmental deregulation of prices changed, with the comparison also taking into account distance of haul, goods hauled, and the price of diesel fuel.
Define an experiment-wise error rate.
Drafting NFL quarterbacks. Refer to the Journal of Productivity Analysis (Vol. 35, 2011) study of how successful NFL teams are in drafting productive quarterbacks, Exercise 1.26 (p. 51). Recall that the researchers measured two variables for each of the 331 quarterbacks drafted between
1970 and 2007: (1) Draft position (Top 10, between picks 11 and 50, or after pick 50) and (2) QB production score (where higher scores indicate more productive QBs). Suppose we want to compare the mean production score
of quarterbacks in the three draft position groups. Identify each of the following elements for this study:
a. Response variable
b. Factor(s)
c. Treatments
d. Experimental units
Mixed gender decision-making groups. In business, a group of executives is often assigned to make key decisions. The American Journal of Political Science (April 2014) published a study on a woman’s impact on mixed-gender deliberating groups. The researchers randomly assigned subjects to one of several 5-member decision-making groups. The
groups’ gender composition varied as follows: 0 females, 1 female, 2 females, 3 females, 4 females, or 5 females. Each group was then randomly assigned to utilize one of two types of decision rules: unanimous or majority rule. Ten groups were created for each of the 6 * 2 = 12 combinations of gender composition and decision rule. One variable
of interest, measured for each group, was the number of words spoken by women on a certain topic per 1,000 total words spoken during the deliberations.
a. Why is this experiment considered a designed study?
b. Identify the experimental unit and dependent variable in this study.
c. Identify the factors for this study. Give the levels of each factor.
d. How many treatments are in this study? List them.
Robots trained to behave like ants. Robotic researchers investigated whether robots could be trained to behave like ants in an ant colony (Nature, August 2000). Robots were trained and randomly assigned to “colonies” (i.e., groups) consisting of 3, 6, 9, or 12 robots. The robots were assigned the task of foraging for “food” and to recruit another robot when they identified a resource-rich area. One goal of the experiment was to compare the mean energy expended (per robot) of the four different colony sizes.
a. What type of experimental design was employed?
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