- The document analyzes data from an "Escalafon.txt" file containing 200 observations of staff ranked from 1 to 14. - Summary statistics are calculated and graphs are generated showing the distribution of ranks and number of staff within each rank. - Additional analysis includes calculating quantiles and summary statistics for sample data.

1. > datos=read.table("Escalafon.txt")
> attach(datos)
> datos
V1
1 1
2 1
3 1
4 1
5 1
6 1
7 1
8 1
9 1
10 1
11 1
12 1
13 1
14 2
15 2
16 2
17 2
18 2
19 2
20 2
21 2
22 2
23 2
24 2
25 2
26 2
27 3
28 3
29 3
30 3
31 3
32 3
33 3
34 3
35 3
36 3
37 3
38 3
39 3
40 4
41 4
42 4
43 4
44 4

2. 45 4
46 4
47 4
48 4
49 4
50 4
51 4
52 2
53 5
54 5
55 5
56 5
57 5
58 5
59 5
60 5
61 5
62 5
63 5
64 3
65 3
66 6
67 6
68 6
69 6
70 6
71 6
72 6
73 6
74 6
75 6
76 6
77 6
78 6
79 7
80 7
81 7
82 7
83 7
84 7
85 7
86 7
87 7
88 7
89 7
90 7
91 2
92 8

3. 93 8
94 8
95 8
96 8
97 8
98 8
99 8
100 8
101 8
102 8
103 9
104 9
105 9
106 9
107 9
108 9
109 9
110 9
111 9
112 9
113 9
114 9
115 9
116 9
117 9
118 10
119 10
120 10
121 10
122 10
123 10
124 10
125 10
126 10
127 10
128 9
129 9
130 3
131 11
132 11
133 11
134 11
135 11
136 11
137 11
138 11
139 11
140 1

4. 141 1
142 1
143 12
144 12
145 12
146 12
147 12
148 12
149 12
150 12
151 12
152 12
153 12
154 12
155 12
156 12
157 13
158 13
159 13
160 13
161 13
162 13
163 13
164 13
165 2
166 2
167 2
168 3
169 3
170 14
171 14
172 14
173 14
174 14
175 14
176 14
177 1
178 1
179 1
180 1
181 1
182 1
183 2
184 2
185 2
186 3
187 3
188 3

5. 189 2
190 2
191 2
192 2
193 2
194 2
195 9
196 9
197 9
198 9
199 9
200 9
> f=table(datos)
> f
datos
1 2 3 4 5 6 7 8 9 10 11 12 13 14
22 27 21 12 11 13 12 11 23 10 9 14 8 7
> n=sum(f)
> n
[1] 200
> h=(f/n)*100
> h
datos
1 2 3 4 5 6 7 8 9 10 11 12 13 14
11.0 13.5 10.5 6.0 5.5 6.5 6.0 5.5 11.5 5.0 4.5 7.0 4.0 3.5
> F=cumsum(f)
> F
1 2 3 4 5 6 7 8 9 10 11 12 13 14
22 49 70 82 93 106 118 129 152 162 171 185 193 200
> H=cumsum(h)
> H
1 2 3 4 5 6 7 8 9 10 11 12 13 14
11.0 24.5 35.0 41.0 46.5 53.0 59.0 64.5 76.0 81.0 85.5 92.5 96.5 100.0

6. > cbind(f,h,F,H)
f h F H
1 22 11.0 22 11.0
2 27 13.5 49 24.5
3 21 10.5 70 35.0
4 12 6.0 82 41.0
5 11 5.5 93 46.5
6 13 6.5 106 53.0
7 12 6.0 118 59.0
8 11 5.5 129 64.5
9 23 11.5 152 76.0
10 10 5.0 162 81.0
11 9 4.5 171 85.5
12 14 7.0 185 92.5
13 8 4.0 193 96.5
14 7 3.5 200 100.0
> summary(datos)
V1
Min. : 1.00
1st Qu.: 3.00
Median : 6.00
Mean : 6.34
3rd Qu.: 9.00
Max. : 14.00
> boxplot(datos, main="Grados de Escalafon", xlab="Escalafon", ylab="Numero de docentes")
> boxplot(datos, notch=TRUE, col=(c("darkgreen")), main="Grados de escalafon", xlab="Docentes")

7. datos1=c(1,2,3,4,5,6,7,8,9,10,11,12,13,14,2,9,1,2,3,4,5,6,7,8,9,10,11,12,13,14,2,9,1,2,3,4,5,6,7,8,9,10,11,12,13,14,3,9)
quantile(datos1, prob = seq(0, 1, length = 11), type = 5)
0% 10% 20% 30% 40% 50% 60% 70% 80% 90% 100%
1.0 2.0 3.0 4.0 6.0 7.5 9.0 10.0 11.0 13.0 14.0
quantile(datos1)
0% 25% 50% 75% 100%
1.00 3.75 7.50 10.25 14.00
quantile(datos1, prob = c(0.15, 0.25, 0.35))
15% 25% 35%
2.05 3.75 5.00
quantile(datos1, prob = c(0.2,0.4,0.6,0.8))
20% 40% 60% 80%
3 6 9 11
em=c(16,17,22,21,27,19,22,31,15,19,22,19,20,18,18,19,16,18,16,21)
eh=c(13,12,22,21,22,18,22,27,15,10,11,19,20,18,17,19,36,18,19,20)
boxplot(em,eh)
datos2=cbind(em,eh)
summary(datos2)
em eh
Min. :15.00 Min. :10.00
1st Qu. :17.75 1st Qu. :16.50
Median :19.00 Median :19.00
Mean :19.80 Mean :18.95
3rd Qu. :21.25 3rd Qu.:21.25
Max. :31.00 Max. :36.00

8. f=table(em)
f
em
15 16 17 18 19 20 21 22 27 31
1 3 1 3 4 1 2 3 1 1
f=table(eh)
f
eh
10 11 12 13 15 17 18 19 20 21 22 27 36
1 1 1 1 1 1 3 3 2 1 3 1 1