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Chapter 9: Q6E (page 528)

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

Short Answer

Expert verified

d. The experimental unit is a quarterback in an NFL team.

Step by step solution

01

Given Information

A study of how successful NFL teams are in drafting productive quarterbacks is provided.

02

Definition

An experimental unit is an object on which the response and factors are observed or measured.

03

Identifying the experimental unit

d.

The experiment is regarding the success of NFL teams in drafting productive quarterbacks. The measurements on the quarterback production score are taken.

Therefore, the experimental unit is a quarterback in an NFL team.

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Most popular questions from this chapter

Forecasting electrical consumption. Two different methods of forecasting monthly electrical consumption were compared and the results published in Applied Mathematics and Computation (Vol. 186, 2007). The two methods were Artificial Neural Networks (ANN) and Time Series Regression (TSR). Forecasts were made using each method for each of 4 months. These forecasts were also compared with the actual monthly consumption values. A layout of the design is shown in the next table. The researchers want to compare the mean electrical consumption values of the ANN forecast, TSR forecast, and Actual consumption

a. Identify the experimental design employed in the study.

Evaluation of flexography printing plates. Refer to the Journal of Graphic Engineering and Design (Vol. 3, 2012) study of the quality of flexography printing, Exercise 9.24 (p. 544). Recall that four different exposure times were studied—8, 10, 12, and 14 minutes—and that the measure of print quality used was dot area (hundreds of dots per square millimeter). Tukey’s multiple comparisons procedure (at an experimentwise error rate of .05) was used to rank the mean dot areas of the four exposure times. The results are summarized below. Which exposure time yields the highest mean dot area? Lowest?

What is the difference between an observational experiment and a designed experiment?

Performance of a bus depot. Refer to the International Journal of Engineering Science and Technology (February 2011) study of public bus depot performance, Exercise 9.25 (p. 544). Recall that 150 customers provided overall performance ratings at each of three different bus depots (Depot 1, Depot 2, and Depot 3). The average performance scores were determined to be significantly different at α=.05 using an ANOVA F-test. The sample mean performance scores were reported as . The researchers employed the Bonferroni method to rank the three performance means using an experiment wise error rate of .05. Adjusted 95% confidence intervals for the differences between each pair of treatment means are shown in the table. Use this information to rank the mean performance scores at the three bus depots.

What are the treatments for a designed experiment that uses one qualitative factor with four levels—A, B, C, and D?
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