## Related questions with answers

Previous studies have shown that urban bus drivers have an extremely stressful job, and a large proportion of drivers retire prematurely with disabilities due to occupational stress. These stresses come from a combination of physical and social sources such as traffic congestion, incessant time pressure, and unruly passengers. In the paper, “Hassles on the Job: A Study of a Job Intervention With Urban Bus Drivers” (Journal of Organizational Behavior, Vol. 20, pp. 199-208), G. Evans et al. examined the effects of an intervention program to improve the conditions of urban bus drivers. Among other variables, the researchers monitored diastolic blood pressure of bus drivers in downtown Stockholm, Sweden. The data, in millimeters of mercury (mm Hg), on the WeissStats CD are based on the blood pressures obtained prior to intervention for the 41 bus drivers in the study. Use the technology of your choice to do the following. a. Obtain a normal probability plot, boxplot, histogram, and stem-and-leaf diagram of the data. b. Based on your results from part (a), can you reasonably apply the one-mean t-test to the data? Explain your reasoning. c. At the 10% significance level, do the data provide sufficient evidence to conclude that the mean diastolic blood pressure of bus drivers in Stockholm exceeds the normal diastolic blood pressure of 80 mm Hg?

Solution

VerifiedGiven:

$\begin{align*} n&=\text{Sample size}=41 \\ \alpha&=\text{Significance level}=10\%=0.10 \end{align*}$

(a) $\textbf{Normal probability plot}$

The data values are on the horizontal axis and the standardized normal scores are on the vertical axis.

If the data contains $n$ data values, then the standardized normal scores are the z-scores in the normal probability table of the appendix corresponding to an area of $\dfrac{j-0.5}{n}$ (or the closest area) with $j\in \{1,2,3,....,n\}$.

The smallest standardized score corresponds with the smallest data value, the second smallest standardized score corresponds with the second smallest data value, and so on.

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