12.25. Sleep deprivation and reaction times. Sleep deprivation experienced by ph

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12.25. Sleep deprivation and reaction times. Sleep deprivation experienced by physicians during residency training and the possible negative consequences are of concern to many in health care. One study of 33 resident anesthesiologists compared their changes from baseline in reaction times on four tasks.8 Under baseline conditions, the physicians reported getting an average of 7.04 hours of sleep. While on duty, however, the average was 1.66 hours. For each of the tasks, the researchers reported a statistically significant increase in the reaction time when the residents were working in a state of sleep deprivation. a day. When the alarm sounded, participants recorded time immediately preceding the alarm. These responses number of emotions recorded, ex scale of 0 to 6. At the ood ratings indicating their emotions for the 12.33. Writing contrasts. Return to the eye study described in Example 12.25 (page 579). Let 1, 2, 3, and 4 represent the mean scores for blue, brown, gaze down as a percent; and (a) Because a majority of the population sampled is Hispanic compare the average score of the brown eyes with the average of the other two eye colors. Write a contrast that asked to re call the percent of (eye color predominantly brown), we want to time that t variable was called "recall." Here is a Chapter 12 Exercises 587 (b) Write a contrast to compare the average score when the model is looking at you versus the score when looking 12.36. ANOVA. The two- t and one-way xercise 7.67 (page 414). In that you were asned to calculate the pooled t statistic

Explanation / Answer

12.33 (a) :

The best way to compare averages of similar random variables is to use arithmetic difference. So, a good contrast fucntion would be Contrast(Colour) = µ2 - ((µ1 + µ4)/2)  

12.33 (b)

By 'when the model looking at you', I assume it includes all the recorded eye colour observations (blue, brown and green). But we cannot just sum up the averages, instead we must average these colour averages and then subtract from the 'not looking average' to get contrast. So the contrast function would be Contrast(Looking) = ((µ1 + µ2+ µ4)/3) - µ3.

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