For Exercises 51 through 54 , you should use the following definition of an outlier: An outlier is any data value that is above the third quartile by more than 1.5 times the IQR [Outlier> Q 3 + l.5(IQR)] or below the first quartile by more than 1.5 times the IQR [Outlier < Q 1 — l.5(IQR)]. (Note: There is no one universally agreed upon definition of an outlier; this is but one of several definitions used by statisticians.) Using the preceding definition, find the outliers (if there are any) in the City of Cleansburg Fire Department data set discussed in Exercises 30 and 37 . (Hint: Do Exercise 37 first.) Table 15-20 shows ages of the firefighters in the Cleansburg fire department. Table 15-20 Age 25 27 28 29 30 Frequency 2 7 6 9 15 Age 31 32 33 37 39 Frequency 12 9 9 6 4 For Exercises 51 through 54 , you should use the following definition of an outlier: An outlier is any data value that is above the third quartile by more than 1.5 times the IQR [Outlier> Q 3 + l.5(IQR)] or below the first quartile by more than 1.5 times the IQR [Outlier < Q 1 — l.5(IQR)]. (Note: There is no one universally agreed upon definition of an outlier; this is but one of several definitions used by statisticians.) Using the preceding definition, find the outliers (if there are any) in the City of Cleansburg Fire Department data set discussed in Exercises 30 and 37 . (Hint: Do Exercise 37 first.) Table 15-20 shows ages of the firefighters in the Cleansburg fire department. Table 15-20 Age 25 27 28 29 30 Frequency 2 7 6 9 15 Age 31 32 33 37 39 Frequency 12 9 9 6 4
For Exercises 51 through 54 , you should use the following definition of an outlier: An outlier is any data value that is above the third quartile by more than 1.5 times the IQR [Outlier> Q 3 + l.5(IQR)] or below the first quartile by more than 1.5 times the IQR [Outlier < Q 1 — l.5(IQR)]. (Note: There is no one universally agreed upon definition of an outlier; this is but one of several definitions used by statisticians.) Using the preceding definition, find the outliers (if there are any) in the City of Cleansburg Fire Department data set discussed in Exercises 30 and 37 . (Hint: Do Exercise 37 first.) Table 15-20 shows ages of the firefighters in the Cleansburg fire department. Table 15-20 Age 25 27 28 29 30 Frequency 2 7 6 9 15 Age 31 32 33 37 39 Frequency 12 9 9 6 4 For Exercises 51 through 54 , you should use the following definition of an outlier: An outlier is any data value that is above the third quartile by more than 1.5 times the IQR [Outlier> Q 3 + l.5(IQR)] or below the first quartile by more than 1.5 times the IQR [Outlier < Q 1 — l.5(IQR)]. (Note: There is no one universally agreed upon definition of an outlier; this is but one of several definitions used by statisticians.) Using the preceding definition, find the outliers (if there are any) in the City of Cleansburg Fire Department data set discussed in Exercises 30 and 37 . (Hint: Do Exercise 37 first.) Table 15-20 shows ages of the firefighters in the Cleansburg fire department. Table 15-20 Age 25 27 28 29 30 Frequency 2 7 6 9 15 Age 31 32 33 37 39 Frequency 12 9 9 6 4
Solution Summary: The author calculates the number of firefighters in the Cleansburg fire department. The first quartile is the 20th firefighter.
For Exercises 51 through 54, you should use the following definition of an outlier: An outlier is any data value that is above the third quartile by more than 1.5 times the IQR [Outlier>
Q
3
+ l.5(IQR)] or below the first quartile by more than 1.5 times the IQR [Outlier <
Q
1
— l.5(IQR)]. (Note: There is no one universally agreed upon definition of an outlier; this is but one of several definitions used by statisticians.)
Using the preceding definition, find the outliers (if there are any) in the City of Cleansburg Fire Department data set discussed in Exercises 30 and 37. (Hint: Do Exercise 37 first.)
Table 15-20 shows ages of the firefighters in the Cleansburg fire department.
Table 15-20
Age
25
27
28
29
30
Frequency
2
7
6
9
15
Age
31
32
33
37
39
Frequency
12
9
9
6
4
For Exercises 51 through 54, you should use the following definition of an outlier: An outlier is any data value that is above the third quartile by more than 1.5 times the IQR [Outlier>
Q
3
+ l.5(IQR)] or below the first quartile by more than 1.5 times the IQR [Outlier <
Q
1
— l.5(IQR)]. (Note: There is no one universally agreed upon definition of an outlier; this is but one of several definitions used by statisticians.)
Using the preceding definition, find the outliers (if there are any) in the City of Cleansburg Fire Department data set discussed in Exercises 30 and 37. (Hint: Do Exercise 37 first.)
Table 15-20 shows ages of the firefighters in the Cleansburg fire department.
A: Tan Latitude / Tan P
A = Tan 04° 30'/ Tan 77° 50.3'
A= 0.016960 803 S CA named opposite to latitude,
except when hour angle between 090° and 270°)
B: Tan Declination | Sin P
B Tan 052° 42.1'/ Sin 77° 50.3'
B = 1.34 2905601 SCB is alway named same as
declination)
C = A + B = 1.35 9866404 S CC correction, A+/- B:
if A and B have same name - add, If
different name- subtract)
=
Tan Azimuth 1/Ccx cos Latitude)
Tan Azimuth = 0.737640253
Azimuth
=
S 36.4° E CAzimuth takes combined
name of C correction and Hour Angle - If LHA
is between 0° and 180°, it is named "west", if
LHA is between 180° and 360° it is named "east"
True Azimuth= 143.6°
Compass Azimuth = 145.0°
Compass Error = 1.4° West
Variation 4.0 East
Deviation: 5.4 West
A: Tan Latitude / Tan P
A = Tan 04° 30'/ Tan 77° 50.3'
A= 0.016960 803 S CA named opposite to latitude,
except when hour angle between 090° and 270°)
B: Tan Declination | Sin P
B Tan 052° 42.1'/ Sin 77° 50.3'
B = 1.34 2905601 SCB is alway named same as
declination)
C = A + B = 1.35 9866404 S CC correction, A+/- B:
if A and B have same name - add, If
different name- subtract)
=
Tan Azimuth 1/Ccx cos Latitude)
Tan Azimuth = 0.737640253
Azimuth
=
S 36.4° E CAzimuth takes combined
name of C correction and Hour Angle - If LHA
is between 0° and 180°, it is named "west", if
LHA is between 180° and 360° it is named "east"
True Azimuth= 143.6°
Compass Azimuth = 145.0°
Compass Error = 1.4° West
Variation 4.0 East
Deviation: 5.4 West
Direction: Strictly write in 4 bond paper, because my activity
sheet is have 4 spaces. This is actually for maritime.
industry course, but I think geometry can do this.
use nautical almanac.
Sample Calculation (Amplitude- Sun):
On 07th May 2006 at Sunset, a vesel in position 10°00'N
0 10°00' W observed the sun bearing 288° by compass. Find
the
compass error.
LMT Sunset
07d
18h
13m
(+)00d
00h
40 м
LIT:
UTC Sunset:
07d
18h
53 m
added - since
longitude is
westerly
Declination Co7d 18h): N016° 55.5'
d(0.7):
(+)
00-6
N016 56.1'
Declination Sun:
Sin Amplitude Sin Declination (Los Latitude
- Sin 016° 56.1'/Cos 10°00'
= 0.295780189
Amplitude = WI. 2N (The prefix of amplitude is
named easterly if body is rising.
and westerly of body is setting.
The suffix is named came as
declination.)
True Bearing: 287.20
Compass Bearing
288.0°
Compass Error: 0.8' West
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