Chapter 1: Q11. (page 49)
Give an example of unethical statistical practice.
Short Answer
A company intentionally discarding certain information from its sales data in a specific year can be regarded as an unethical statistical practice.
Chapter 1: Q11. (page 49)
Give an example of unethical statistical practice.
A company intentionally discarding certain information from its sales data in a specific year can be regarded as an unethical statistical practice.
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Get started for freeInspection of highway bridges. All highway bridges in the United States are inspected periodically for structural deficiency by the Federal Highway Administration (FHWA). Data from the FHWA inspections are compiled into the National Bridge Inventory (NBI). Several of the nearly 100 variables maintained by the NBI are listed below. Classify each variable as quantitative or qualitative.
a. Length of maximum span (feet)
b. Number of vehicle lanes
c. Toll bridge (yes or no)
d. Average daily traffic
e. Condition of deck (good, fair, or poor)
f. Bypass or detour length (miles)
g. Route type (interstate, U.S., state, county, or city)
Question: Performance-based logistics. In industry, performance-based logistics (PBL) strategies are increasingly popular ways to reduce cost, increase revenue, and attain customer satisfaction. The Journal of Business Logistics (Vol. 36, 2015) used the opinions of a sample of 17 upper-level employees of the U.S. Department of Defense and its suppliers to determine the factors that lead to successful PBL projects. The current position (e.g., vice president, manager [mgr.]), type of organization (commercial or government), and years of experience were measured for each employee interviewed. These data are listed below. Identify each variable measured as producing quantitative or qualitative data.
Interviews | Position | Organization | Experience (years) |
1 | Vice president | Commercial | 30 |
2 | Post production | Government | 15 |
3 | Analyst | Commercial | 10 |
4 | Senior mgr. | Government | 30 |
5 | Support chief | Commercial | 30 |
6 | Specialist | Government | 25 |
7 | Senior analyst | Government | 9 |
8 | Division chief | Government | 6 |
9 | Item mgr. | Government | 3 |
10 | Senior mgr. | Government | 20 |
11 | MRO mgr. | Government | 25 |
12 | Logistics mgr. | Government | 30 |
13 | MRO mgr. | Commercial | 10 |
14 | MRO mgr. | Commercial | 5 |
15 | MRO mgr. | Commercial | 10 |
16 | Specialist | Government | 20 |
17 | Chief | Government | 25 |
Explain how populations and samples differ?
The “lucky store effect” in lottery ticket sales. In the American Economic Review (Vol. 98, 2008), University of Chicago researchers investigated the lucky store effect theory in lottery ticket sales, i.e., the theory that a lottery retail store that sold a large-prize-winning ticket will experience greater ticket sales the following week. The researchers examined the weekly ticket sales of all 24,400 active lottery retailers in Texas. The analysis showed that “the week following the sale of [a winning Lotto Texas ticket], the winning store experiences a 12 to 38 percent relative sales increase. . . . ” Consequently, the researchers project that future winning lottery retail stores will experience the lucky store effect. Is this study an example of descriptive statistics or inferential statistics? Explain.
Explain the difference between quantitative and qualitative data?
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