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which had already been reported to the ASRS.
Total and Percent Distributions
Multiple entries are permitted in many of the data
fields coded by ASRS analysts. For example, an altitude
bust that resulted in a loss of standard separation
would be coded in the Anomaly field as an
altitude deviation, an airborne conflict, and an ATC
clearance violation. While this is the most accurate
way of coding events, it means that incidents do not
fall into neat, mutually exclusive categories that always
add up to 100 percent. Moreover, it is not unusual
for selected data fields to be left blank during
coding, either because needed information is not
available, or because the field is not deemed relevant
to a particular report. This presents an added complication
when incidents are totaled and percent distributions
are calculated.
The first chart in the following pages shows the
number of unique incidents reported to the ASRS
over the past 7 years. This provides a baseline for interpreting
data in succeeding charts which characterize
the time, location, and other aspects of the
reported incidents. The data in these latter tables are
presented in a consistent format that provides for unknown
or inapplicable data, and for cases in which
more than one category applies. An example is shown
below in the hypothetical table.
In this example, incident records are categorized as
A, B, or C. Any incident may be placed in one, two, or
even three of these categories. If categories A, B, and
C are simply added together, incidents that are recorded
in more than one category will be doublecounted
in the “Total Row.” Since double-counting is
usually unwanted in summations, the totals have
been adjusted to eliminate double-counted events.
The results are presented in the row entitled Total
Unique Incidents.
Thus, in the Hypothetical Example Table, a total of
165 incidents were reported during the current time
period. This is the Incident Base for that period. Out
of the Incident Base, 127 unique events fell into categories
A, B, or C, or some combination of these categories.
The remaining 38 incidents did not fit any of
the categories, or there was insufficient data to classify
them. These are shown in the Inapplicable or Unknown
row.
Because the number of Total Unique Incidents varies
from table to table, we decided to use the Incident
Base to calculate percent distributions for all data sets.
By calculating the percentages in this matter, we created
a common yardstick which can be used to compare
the data presented in the various charts.
Finally, all of the percentages shown were rounded
to whole numbers. In those cases where the number
of relevant incidents is very small (less than one-half
of one percent) the percentages round down to, and
are presented as, zero percent. Similarly, in those
cases where the number of reports in a category exceed
99.5 percent of the Incident Base, the result was
rounded up to, and is presented as, 100 percent. _
Hypothetical Example Table
Data Category
1993 Jan ’87 through Dec ’93
Incidents%of Incident BaseIncidents% of Incident Base
Category A 22 13% 1,207 12%
Category B 39 24% 2,945 29%
Category C 83 50% 5,352 52%
Total Unique Incidents 127 77% 7,698 75%
Inapplicable or Unknown 38 23% 2,509 25%
Incident Base 165 100% 10,207 100%
22 Issue Number 8
30,000
25,000
20,000
15,000
10,000
5,000
0
1988 1989 1990 1991 1992 1993 1994
Period of Occurrence Year Total Cumulative
Reported Incidents
1988
1989
1990
1991
1992
1993
1994
16,384
24,953
27,731
25,037
25,869
24,411
26,413
16,384
41,337
69,068
94,105
119,974
144,385
170,798 Incident Base
Year of Occurrence
Issue Number 8 23
70%
0%
Pilot/
Air Carrier
Reporters
Pilot/Air Carrier
Pilot/General Aviation
Pilot/Other
Controller
All Other
Total Unique Relevant
Incident Base
Pilot/
General Aviation
Pilot/
Other
Controller All Other
1994
1988 through 1994
60%
50%
40%
30%
20%
10%
Incidents % of Incident Base Incidents % of Incident Base
1994 1988 through 1994
Irrelevant or Unknown
16,996
7,196
1,040
986
296
26,375
26,413
38
108,110
49,023
6,140
6,888
1,271
170,607
　
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