Final answer:
To evaluate the accuracy of the AAA's claim that driver error causes 54% of fatal auto accidents, a hypothesis test comparing the sample proportion from 30 accidents to the AAA proportion would be conducted, with the significance level set at 0.05. The context of driver safety and traffic fatalities is critical for understanding and addressing risks on the road.
Step-by-step explanation:
In referencing the 1,164 traffic fatalities in Georgia in 2014 where the majority were drivers, we can connect this to a broader discussion about traffic safety and statistical analysis. According to the data given, driver error accounts for approximately 54% of all fatal auto accidents, as stated by the American Automobile Association (AAA). When assessing the accuracy of the AAA proportion, a hypothesis test can be conducted with a significance level of α = 0.05. In a sample of 30 fatal accidents, it is found that driver error caused 14 of them. To determine if the AAA proportion is accurate, one would use a binomial test comparing the sample proportion with the reported AAA proportion.
Understanding trends in traffic safety can be further exemplified by the total number of fatal motor vehicle traffic crashes listed in Table 1.19 for the years 1994-2011. With the changing landscape of risks over years, such as increases in drug overdose deaths surpassing fatal car crash statistics, it emphasizes the ongoing need to analyze and address different safety concerns.
The discussion on proportions also extends to analyzing the risk of head injuries in crash scenarios. Studies like the one where 75 cars with dummies crashed into a wall at 35 mph help predict driver safety outcomes. Consistent evaluation and studies regarding traffic fatalities are crucial to improving road safety and reducing accident rates.