# The Manager's Guide to Statistics Summarizing and Displaying Data

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Chapter 1 Exercise 6:

As the question states, pharmaceutical companies sponsor drug safety research studies. This, however, is not an example of a confounding factor. Confounding factors occur when the groups the study is comparing may have a secondary characteristic beyond the one you are comparing. This is not to say that the sponsoring of studies by drug companies is not a risk of a conflict of interest.

Chapter 1 Exercise 13:

Initially, someone may review the data in the chart and decide that “Driver/sales workers and truck drivers” is the most dangerous with the most deaths. However, it is important to factor in the rate of deaths vs those employed. In the attached chart, we see that in fact “Fishers and fishing workers” is in fact the most dangerous occupation with 1 death for every 845 employees vs that of “Driver/sales workers and truck drivers” with a rate of 1 death for every 3437 employees.

Occupation Deaths # Employed Fatality Rate (1 per x)

Fishers and fishing workers 48 40540 844.5833

Logging Workers 80 86110 1076.3750

Aircraft Pilots 81 121070 1494.6914

Structural iron and steel workers 35 62940 1798.2857

Refuse and recyclable material collectors 32 73050 2282.8125

Farmers and ranchers 341 829680 2433.0792

Electrical power line installers/repairers 36 110090 3058.0556

Driver/Sales Workers and truck drivers 993 3412370 3436.4250

Miscellaneous Agricultural workers 176 758620 4310.3409

Construction laborers 339 1493390 4405.2802

It is important to note that this study would be considered an observational study because there are many confounding factors. For example, king crab fishing is exceptionally more dangerous than other kinds of fishing. There are also other factors such as the age and general heath of the employees on the job and the location their job is.

Chapter 1 Exercise 15:

The Harvard Business Review article “When to Sleep on IT” found that participants who made immediate decisions made better decisions than those who took longer to make the decision. This is an observational study because it is a review of two naturally formed groups rather than experimental because there was no usage of adjusting for or controlling for to control confounding factors. One such confounding factor would be at what age and experience level the subjects participating in the study were. Another related confounding factor would be the relationship between the subject’s experience and the decision to be made. Someone with more experience in the decision’s subject may come up with a correct answer more immediately than someone with less experience. A way to re-design this study to adjust for and control these factors would be to break it down into smaller subgroups based on age and occupation.

Chapter 2 Exercise 33:

Using the excel formula stdev.p() we can find the standard deviation of each stock to determine the stock with the highest price variability. The stock with the highest price variability was ZTH with a standard deviation of 16.733. Using the Excel formula for average() we can find the stock with the highest average price. The stock price with the highest average price was SEKO 308.955.

SEKO ZTH

Average 308.96 213.55

Std Dep 5.9983 16.733

Chapter 2 Exercise 35:

Amount (\$) Orders

Under 1000 61

1100 44

1200 63

1300 94

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