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For security, we also emphasize a statistical perspective. But we will see that what we
can learn from data analysis is less clear than for safety. The discussion is sometimes
tentative, and it serves to remind us of the difficulties that policy makers face every
day. Yet neither they nor we can simply throw up our hands and declare security an
intractable problem: decisions have to be made, and decisions based on imperfect but
reasoned analyses would seem preferable to arbitrary choices. We will depict how some
such analyses are being attempted today.
11.1 Safety
We begin our discussion of aviation safety in the next section, where we discuss a variety
of ways to measure the mortality risk of passenger air travel. In Section 11.1.2, we settle
on a “death risk per flight” metric (the Q-statistic) that, we will argue, has numerous
features that make it a metric of choice. We then calculate Q-statistics in various settings
in Sections 11.1.3, 11.1.4 and 11.1.5, and distinguish between comparative judgments
about aviation safety that deserve to be taken seriously from others that should probably
not be. In Section 11.1.6, we synthesize various statistical clues about the risk of airport
runway collisions in the decades ahead; in Section 11.1.7, we move on to midair collisions.
11.1.1 Measuring Air Safety: Some Hazards
In this section, we assume that the air traveler’s greatest fear is of being killed in a crash.
It follows that statistics about the likelihood of that outcome are of inherent interest. But
which particular statistics are most illuminating about passenger death risk is not obvious,
as is made clear by a review of some of the indicators that are currently available.
The US National Transportation Safety Board (NTSB), for example, has advanced the
statistic fatal accidents per 100 000 hours flown . In general terms, this indicator makes
sense: it relates the number of adverse events to the amount of flying performed. It
therefore provides something of a “cost -benefit” ratio.
Unfortunately, both the numerator and the denominator of the ratio are problematic.
The term “fatal accident” obliterates the distinction between a crash that kills 1 person
out of 300 on board and another that kills 300 out of 300. And the measure gives no
weight to safety improvements (e.g., fire-retardant materials) that reduce fatalities but do
not prevent them.
For security, we also emphasize a statistical perspective. But we will see that what we
can learn from data analysis is less clear than for safety. The discussion is sometimes
tentative, and it serves to remind us of the difficulties that policy makers face every
day. Yet neither they nor we can simply throw up our hands and declare security an
intractable problem: decisions have to be made, and decisions based on imperfect but
reasoned analyses would seem preferable to arbitrary choices. We will depict how some
such analyses are being attempted today.
11.1 Safety
We begin our discussion of aviation safety in the next section, where we discuss a variety
of ways to measure the mortality risk of passenger air travel. In Section 11.1.2, we settle
on a “death risk per flight” metric (the Q-statistic) that, we will argue, has numerous
features that make it a metric of choice. We then calculate Q-statistics in various settings
in Sections 11.1.3, 11.1.4 and 11.1.5, and distinguish between comparative judgments
about aviation safety that deserve to be taken seriously from others that should probably
not be. In Section 11.1.6, we synthesize various statistical clues about the risk of airport
runway collisions in the decades ahead; in Section 11.1.7, we move on to midair collisions.
11.1.1 Measuring Air Safety: Some Hazards
In this section, we assume that the air traveler’s greatest fear is of being killed in a crash.
It follows that statistics about the likelihood of that outcome are of inherent interest. But
which particular statistics are most illuminating about passenger death risk is not obvious,
as is made clear by a review of some of the indicators that are currently available.
The US National Transportation Safety Board (NTSB), for example, has advanced the
statistic fatal accidents per 100 000 hours flown . In general terms, this indicator makes
sense: it relates the number of adverse events to the amount of flying performed. It
therefore provides something of a “cost -benefit” ratio.
Unfortunately, both the numerator and the denominator of the ratio are problematic.
The term “fatal accident” obliterates the distinction between a crash that kills 1 person
out of 300 on board and another that kills 300 out of 300. And the measure gives no
weight to safety improvements (e.g., fire-retardant materials) that reduce fatalities but do
not prevent them.
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