Loading...
Motorcycle-safety courses, offered by a number of organizations, teach motorcyclists important techniques for handling and for safely sharing the road with other road users. If more motorcyclists took these courses, there would be fewer serious motorcycle accidents. Data show that 92% of the motorcyclists who are involved in a serious motorcycle accident have never taken a motorcycle-safety course.
In assessing whether the data cited provided support for the position taken about motorcyclists' taking the courses, it would be most useful to determine which of the following?
| Text from Passage | Analysis |
| Motorcycle-safety courses, offered by a number of organizations, teach motorcyclists important techniques for handling and for safely sharing the road with other road users. |
|
| If more motorcyclists took these courses, there would be fewer serious motorcycle accidents. |
|
| Data show that 92% of the motorcyclists who are involved in a serious motorcycle accident have never taken a motorcycle-safety course. |
|
The argument starts by explaining what motorcycle safety courses do, then makes a claim that more people taking these courses would reduce accidents, and finally supports this with data showing that most accident victims never took courses.
If more motorcyclists took safety courses, there would be fewer serious motorcycle accidents.
The argument uses correlation data (92% of accident victims never took courses) to support a causal claim (taking courses prevents accidents). The logic assumes that because most accident victims lack training, getting training would prevent accidents.
Evaluate - We need to find what additional information would help us determine whether the 92% statistic actually supports the conclusion that more safety courses would reduce accidents
The argument makes a quantitative claim (92% of accident victims never took courses) and uses it to support a causal claim (more courses would mean fewer accidents). We need to evaluate whether this statistical relationship actually proves causation
For evaluate questions, we look for assumptions the argument makes and think about what information would either strengthen or weaken the conclusion when we know more about it. The key gap here is that knowing 92% of accident victims never took courses doesn't automatically mean courses prevent accidents - we need to know about the overall population of motorcyclists to make that comparison meaningful
This directly addresses the core logical gap in the argument. We know \(\mathrm{92\%}\) of accident victims never took courses, but to determine if this supports the conclusion, we need to know what percentage of the general motorcyclist population has taken courses. If significantly more than \(\mathrm{8\%}\) of all motorcyclists have taken courses, then course-takers are underrepresented in accidents, supporting the conclusion. If only \(\mathrm{8\%}\) or fewer have taken courses, the statistic tells us nothing meaningful about course effectiveness.
Whether riding with passengers is riskier than riding alone doesn't help us evaluate whether the \(\mathrm{92\%}\) statistic supports the conclusion about safety courses. This introduces an entirely different risk factor that's irrelevant to assessing the relationship between course-taking and accident prevention.
Whether different organizations offer different course content doesn't help us evaluate the basic claim that taking courses reduces accidents. Even if courses vary in content, we still need to assess whether the \(\mathrm{92\%}\) statistic supports the general conclusion about course-taking, regardless of which specific organization provided the training.
Knowing that more than \(\mathrm{92\%}\) of accidents involve collisions with other vehicles doesn't help us evaluate whether safety courses prevent accidents. This tells us about the nature of accidents but doesn't address the gap between the \(\mathrm{92\%}\) statistic and the conclusion about course effectiveness.
Whether motorcycle size and speed affect accident risk introduces another variable but doesn't help us assess whether the \(\mathrm{92\%}\) statistic supports the conclusion about safety courses. We still wouldn't know if the statistical relationship between course-taking and accidents is meaningful without knowing the baseline rate of course participation.