Statistics
Autor: fmerphy • November 3, 2016 • Coursework • 1,633 Words (7 Pages) • 688 Views
Frank Nakoh
Chapter 1
- Many drug safety research studies are sponsored by pharmaceutical companies that would financially benefit if the results of the study are favorable. Is this an example of a potential confounding factor? Explain?
If the sample to be tested is selected to favor the results of the drug company, then it would be categorized as a confounding factor, but if instead the drug company is sponsoring a study where the sample is selected randomly and divided into treatment and control groups, the experiment will be fairly analyzed and the results will be somehow realistic
- Below are some data from 2005 for on the job deaths in some dangerous jobs. Which job seems the most dangerous? Which seems the least dangerous? Explain.
Obtain death rate for each of the occupation using the formula,
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Occupation | Total deaths | Total employed | Death rate (per 1000) |
Driver/sales workers and truck drivers | 993 | 3,412,370 | 0.291 |
Farmers and ranchers | 341 | 829,680 | 0.411 |
Construction laborers | 339 | 1,493,390 | 0.227 |
Miscellaneous agricultural workers | 176 | 758,620 | 0.232 |
Aircraft pilots | 81 | 121,070 | 0.669 |
Logging workers | 80 | 86,110 | 0.929 |
Fishers and fishing workers | 48 | 40,540 | 1.184 |
Electrical power line installers/repairs | 36 | 110,090 | 0.327 |
Structural iron and steel workers | 35 | 62,940 | 0.556 |
Refuse and recyclable material collectors | 32 | 73,050 | 0.438 |
After calculating the employee’s deaths per total employees for each group, Fishers and Fishing workers appears to be the most dangerous with a death rate of 1.184 per thousand, but instead the job that appears to be the least dangerous is Construction Laborers with a death rate of 0.227 per thousand. Regardless of having the government data and assume by the data the most and least dangerous, I will think we need different data that shows other types of death’s variables, such as deaths cause by natural causes, aging, health issues, to make the results more realistic.
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