cochesCASO - ZGC
cochesCASO - ZGC
193
tipo_motor cilindros tamaño_mdiametro_capacidad relación_cocaballos_pot consumo_ciuconsumo_carrete
dohc four 130 3.47 2.68 9 111 21 27
dohc four 130 3.47 2.68 9 111 21 27
ohcv six 152 2.68 3.47 9 154 19 26
ohc four 109 3.19 3.4 10 102 24 30
ohc five 136 3.19 3.4 8 115 18 22
ohc five 136 3.19 3.4 8.5 110 19 25
ohc five 136 3.19 3.4 8.5 110 19 25
ohc five 136 3.19 3.4 8.5 110 19 25
ohc five 131 3.13 3.4 8.3 140 17 20
ohc four 108 3.5 2.8 8.8 101 23 29
ohc four 108 3.5 2.8 8.8 101 23 29
ohc six 164 3.31 3.19 9 121 21 28
ohc six 164 3.31 3.19 9 121 21 28
ohc six 164 3.31 3.19 9 121 20 25
ohc six 209 3.62 3.39 8 182 16 22
ohc six 209 3.62 3.39 8 182 16 22
ohc six 209 3.62 3.39 8 182 15 20
l three 61 2.91 3.03 9.5 48 47 53
ohc four 90 3.03 3.11 9.6 70 38 43
ohc four 90 3.03 3.11 9.6 70 38 43
ohc four 90 2.97 3.23 9.41 68 37 41
ohc four 90 2.97 3.23 9.4 68 31 38
ohc four 98 3.03 3.39 7.6 102 24 30
ohc four 90 2.97 3.23 9.4 68 31 38
ohc four 90 2.97 3.23 9.4 68 31 38
ohc four 90 2.97 3.23 9.4 68 31 38
ohc four 122 3.34 3.46 8.5 88 24 30
ohc four 156 3.6 3.9 7 145 19 24
ohc four 92 2.91 3.41 9.6 58 49 54
ohc four 92 2.91 3.41 9.2 76 31 38
ohc four 79 2.91 3.07 10.1 60 38 42
ohc four 92 2.91 3.41 9.2 76 30 34
ohc four 92 2.91 3.41 9.2 76 30 34
ohc four 92 2.91 3.41 9.2 76 30 34
ohc four 92 2.92 3.41 9.2 76 30 34
ohc four 110 3.15 3.58 9 86 27 33
ohc four 110 3.15 3.58 9 86 27 33
ohc four 110 3.15 3.58 9 86 27 33
ohc four 110 3.15 3.58 9 86 27 33
ohc four 110 3.15 3.58 9 101 24 28
ohc four 110 3.15 3.58 9.1 100 25 31
ohc four 111 3.31 3.23 8.5 78 24 29
ohc four 119 3.43 3.23 9.2 90 24 29
dohc six 258 3.63 4.17 8.1 176 15 19
dohc six 258 3.63 4.17 8.1 176 15 19
ohcv twelve 326 3.54 2.76 11.5 262 13 17
ohc four 91 3.03 3.15 9 68 30 31
ohc four 91 3.03 3.15 9 68 31 38
ohc four 91 3.03 3.15 9 68 31 38
ohc four 91 3.03 3.15 9 68 31 38
ohc four 91 3.08 3.15 9 68 31 38
ohc four 122 3.39 3.39 8.6 84 26 32
ohc four 122 3.39 3.39 8.6 84 26 32
ohc four 122 3.39 3.39 8.6 84 26 32
ohc four 122 3.39 3.39 8.6 84 26 32
ohc four 122 3.39 3.39 8.6 84 26 32
ohc four 140 3.76 3.16 8 120 19 27
ohc four 134 3.43 3.64 22 72 31 39
ohc five 183 3.58 3.64 21.5 123 22 25
ohc five 183 3.58 3.64 21.5 123 22 25
ohc five 183 3.58 3.64 21.5 123 22 25
ohc five 183 3.58 3.64 21.5 123 22 25
ohcv eight 234 3.46 3.1 8.3 155 16 18
ohcv eight 234 3.46 3.1 8.3 155 16 18
ohcv eight 308 3.8 3.35 8 184 14 16
ohcv eight 304 3.8 3.35 8 184 14 16
ohc four 140 3.78 3.12 8 175 19 24
ohc four 92 2.97 3.23 9.4 68 37 41
ohc four 92 2.97 3.23 9.4 68 31 38
ohc four 92 2.97 3.23 9.4 68 31 38
ohc four 98 3.03 3.39 7.6 102 24 30
ohc four 110 3.17 3.46 7.5 116 23 30
ohc four 122 3.35 3.46 8.5 88 25 32
ohc four 156 3.58 3.86 7 145 19 24
ohc four 156 3.59 3.86 7 145 19 24
ohc four 156 3.59 3.86 7 145 19 24
ohc four 122 3.35 3.46 8.5 88 25 32
ohc four 122 3.35 3.46 8.5 88 25 32
ohc four 110 3.17 3.46 7.5 116 23 30
ohc four 110 3.17 3.46 7.5 116 23 30
ohc four 97 3.15 3.29 9.4 69 31 37
ohc four 103 2.99 3.47 21.9 55 45 50
ohc four 97 3.15 3.29 9.4 69 31 37
ohc four 97 3.15 3.29 9.4 69 31 37
ohc four 97 3.15 3.29 9.4 69 31 37
ohc four 97 3.15 3.29 9.4 69 31 37
ohc four 97 3.15 3.29 9.4 69 31 37
ohc four 97 3.15 3.29 9.4 69 31 37
ohc four 97 3.15 3.29 9.4 69 31 37
ohc four 97 3.15 3.29 9.4 69 31 37
ohc four 120 3.33 3.47 8.5 97 27 34
ohc four 120 3.33 3.47 8.5 97 27 34
ohcv six 181 3.43 3.27 9 152 17 22
ohcv six 181 3.43 3.27 9 152 17 22
ohcv six 181 3.43 3.27 9 152 19 25
ohcv six 181 3.43 3.27 9 160 19 25
ohcv six 181 3.43 3.27 7.8 200 17 23
ohcv six 181 3.43 3.27 9 160 19 25
l four 120 3.46 3.19 8.4 97 19 24
l four 152 3.7 3.52 21 95 28 33
l four 120 3.46 3.19 8.4 97 19 24
l four 152 3.7 3.52 21 95 25 25
l four 120 3.46 2.19 8.4 95 19 24
l four 152 3.7 3.52 21 95 28 33
l four 120 3.46 2.19 8.4 95 19 24
l four 152 3.7 3.52 21 95 25 25
l four 120 3.46 3.19 8.4 97 19 24
l four 152 3.7 3.52 21 95 28 33
l four 134 3.61 3.21 7 142 18 24
ohc four 90 2.97 3.23 9.4 68 37 41
ohc four 98 3.03 3.39 7.6 102 24 30
ohc four 90 2.97 3.23 9.4 68 31 38
ohc four 90 2.97 3.23 9.4 68 31 38
ohc four 98 2.97 3.23 9.4 68 31 38
ohc four 122 3.35 3.46 8.5 88 24 30
ohc four 156 3.59 3.86 7 145 19 24
ohc four 151 3.94 3.11 9.5 143 19 27
ohcf six 194 3.74 2.9 9.5 207 17 25
ohcf six 194 3.74 2.9 9.5 207 17 25
ohcf six 194 3.74 2.9 9.5 207 17 25
ohc four 121 3.54 3.07 9.31 110 21 28
ohc four 121 3.54 3.07 9.3 110 21 28
ohc four 121 2.54 2.07 9.3 110 21 28
ohc four 121 3.54 3.07 9.3 110 21 28
dohc four 121 3.54 3.07 9 160 19 26
dohc four 121 3.54 3.07 9 160 19 26
ohcf four 97 3.62 2.36 9 69 31 36
ohcf four 108 3.62 2.64 8.7 73 26 31
ohcf four 108 3.62 2.64 8.7 73 26 31
ohcf four 108 3.62 2.64 9.5 82 32 37
ohcf four 108 3.62 2.64 9.5 82 28 33
ohcf four 108 3.62 2.64 9 94 26 32
ohcf four 108 3.62 2.64 9 82 24 25
ohcf four 108 3.62 2.64 7.7 111 24 29
ohcf four 108 3.62 2.64 9 82 28 32
ohcf four 108 3.62 2.64 9 94 25 31
ohcf four 108 3.62 2.64 9 82 23 29
ohcf four 108 3.62 2.64 7.7 111 23 23
ohc four 92 3.05 3.03 9 62 35 39
ohc four 92 3.05 3.03 9 62 31 38
ohc four 92 3.05 3.03 9 62 31 38
ohc four 92 3.05 3.03 9 62 31 37
ohc four 92 3.05 3.03 9 62 27 32
ohc four 92 3.05 3.03 9 62 27 32
ohc four 98 3.19 3.03 9 70 30 37
ohc four 98 3.19 3.03 9 70 30 37
ohc four 110 3.27 3.35 22.5 56 34 36
ohc four 110 3.27 3.35 22.5 56 38 47
ohc four 98 3.19 3.03 9 70 38 47
ohc four 98 3.19 3.03 9 70 28 34
ohc four 98 3.19 3.03 9 70 28 34
ohc four 98 3.19 3.03 9 70 29 34
ohc four 98 3.19 3.03 9 70 29 34
dohc four 98 3.24 3.08 9.4 112 26 29
dohc four 98 3.24 3.08 9.4 112 26 29
ohc four 146 3.62 3.5 9.3 116 24 30
ohc four 146 3.62 3.5 9.3 116 24 30
ohc four 146 3.62 3.5 9.3 116 24 30
ohc four 146 3.62 3.5 9.3 116 24 30
ohc four 146 3.62 3.5 9.3 116 24 30
ohc four 146 3.62 3.5 9.3 116 24 30
ohc four 122 3.31 3.54 8.7 92 29 34
ohc four 110 3.27 3.35 22.5 73 30 33
ohc four 122 3.31 3.54 8.7 92 27 32
ohc four 122 3.31 3.54 8.7 92 27 32
ohc four 122 3.31 3.54 8.7 92 27 32
dohc six 171 3.27 3.35 9.3 161 20 24
dohc six 171 3.27 3.35 9.3 161 19 24
dohc six 171 3.27 3.35 9.2 156 20 24
dohc six 161 3.27 3.35 9.2 156 19 24
ohc four 97 3.01 3.4 23 52 37 46
ohc four 109 3.19 3.4 9 85 27 34
ohc four 97 3.01 3.4 23 52 37 46
ohc four 109 3.19 3.4 9 85 27 34
ohc four 109 3.19 3.4 9 85 27 34
ohc four 97 3.01 3.4 23 68 37 42
ohc four 109 3.19 3.4 10 100 26 32
ohc four 109 3.19 3.4 8.5 90 24 29
ohc four 109 3.19 3.4 8.5 90 24 29
ohc five 136 3.19 3.4 8.5 110 19 24
ohc four 97 3.01 3.4 23 68 33 38
ohc four 109 3.19 3.4 9 88 25 31
ohc four 141 3.78 3.15 9.5 114 23 28
ohc four 141 3.78 3.15 9.5 114 23 28
ohc four 141 3.78 3.15 9.5 114 24 28
ohc four 141 3.78 3.15 9.5 114 24 28
ohc four 130 3.62 3.15 7.5 162 17 22
ohc four 130 3.62 3.15 7.5 162 17 22
ohc four 141 3.78 3.15 9.5 114 23 28
ohc four 141 3.78 3.15 8.7 160 19 25
ohcv six 173 3.58 2.87 8.8 134 18 23
ohc six 145 3.01 3.4 23 106 26 27
ohc four 141 3.78 3.15 9.5 114 19 25
precio_inflacion media_precio_inflacion
33350
40776
40776 38300.6666667
34475
43124
37687
43766
46756
59002 44135
40603
41826
51822
52156
60706
76016
102100
91140 64546.125
12729
15556
16249 14844.6666667
13770
15760
19664
15393
16538
18804
22046
32037 19251.5
16011
16940
13342
16135
17618
18028
18028
19511
22476
21858
25441
31991
25565 20226.4615385
16767
27303 22035
79699
87853
88966 85506
12838
15063
16792
16545
18275
21858
20993
26183
25318
27789
45175
45333 24346.8333333
63146
69808
69631
78092
84478
86632
101223
112195 83150.625
40783 40783
13318
15294
16481
19001
24612
21003
31210
36745
35806
17272
20237
22930
22930 22833.7692308
13590
17544
16431
16926
18161
18038
19274
18532
19767
20385
22115
23598
33359
35584
33359
42504
48681
45469 25739.8333333
29408
32621
30742
34252
38502
41764
41258
42196
41097
44359
44853 38277.4545455
13770
19664
15393
16538
18804
22046
31543 19679.7142857
54412
80386
84092
91506 77599
29285
30075
37168
38329
44853
46015 37620.8333333
12648
17430
18789
17610
19214
24614
22817
27824
18443
25202
19803
28899 21107.75
13217
15663
16034
17096
19518
21692
17146
17788
19518
19246
19122
20655
22879
19913
20358
22978
23571
20879
23820
24685
27676
28541
43665
22113
26438
24683
26932
27796
40919
39535
38774
38923 24430.40625
19214
19708
19758
20253
20993
23465
24701
28655
24663
32856
34214
30372 24904.3333333
31978
33152
39503
40812
45520
46831
41629
47066
53095
55529
55912 44638.8181818
9.19047619048
xi Media 37807.51
coche n Precio_infla xi*n Desvia Estandar (x-m)2
alfa-romero 3 38300.67 114902 4287.40 243199.71
audi 6 44135.00 264810 8531.68 40037081.07
bmw 8 64546.13 516369 22893.32 714953326.62
chevrolet 3 14844.67 44534 1864.70 527292350.43
dodge 8 19251.50 154012 5808.09 344325649.73
honda 13 20226.46 262944 5094.99 309093400.13
isuzu 2 22035.00 44070 7450.08 248772192.92
jaguar 3 85506.00 256518 5059.71 2275145581.69
mazda 12 24346.83 292162 10792.64 181189919.78
mercedes-be 8 83150.63 665205 16778.60 2055997729.41
mercury 1 40783.00 40783 #DIV/0! 8853517.87
mitsubishi 13 22833.77 296839 7520.07 224213027.71
nissan 18 25739.83 463317 11064.80 145628912.88
peugot 11 38277.45 421052 5552.19 220844.26
plymouth 7 19679.71 137758 5919.95 328617116.78
porsche 4 77599.00 310396 16134.52 1583362370.60
saab 6 37620.83 225725 7069.63 34849.61
subaru 12 21107.75 253293 4794.73 278882112.41
toyota 32 24430.41 781773 7920.37 178947007.55
volkswagen 12 24904.33 298852 5383.75 166492067.26
volvo 11 44638.82 491027 8191.36 46666718.97
193
Media 79 75 82
Desvia 9 10 10
Ii fi
[12648 , 23709> 88
[23709 , 34770> 41 Precio_inflacion n=
[34770 , 45831> 34 Alcance A=
[45831 , 56892> 11 núm intervalos de clase K=
[56892 , 67953> 3 K=
[67953 , 79014> 4 K=
[79014 , 90075> 7 K=
[90075 , 101136> 2
[101136 , 112197> 3
193
193
(12648; 112195)
1+3,3 log(n)
1+3,3 log(193)
8.54233912
9
1. Investigue que marca de coche es la más cara. Justifique la respuesta.
La marca de coche más cara es Jaguar, de acuerdo a la media entre todos los
precios de Jaguar, colocando su precio inflación como el más elevado en
comparación a los demás.
Media 37807.51
Precio_infla
jaguar 85506.00
mercedes-be 83150.63 Chart Title
porsche 77599.00
90000
bmw 64546.13
volvo 44638.82 80000
audi 44135.00
mercury 40783.00 70000
alfa-romero 38300.67
60000
peugot 38277.45
saab 37620.83 50000
nissan 25739.83
40000
volkswagen 24904.33
toyota 24430.41 30000
mazda 24346.83
mitsubishi 22833.77 20000
isuzu 22035.00
10000
subaru 21107.75
honda 20226.46 0
i i
plymouth 19679.71 ar z e w o d ry o t
ab an en ta a h
u en h m lv
au u er go sa s yo az
d
is
ag -b rs
c b vo rc m eu is ag b is
u
dodge 19251.50 j es o e o p n w to m u
p m -r ks ts
ed fa l i
chevrolet 14844.67 c al vo m
er
m
Chart Title
Column D
t ta a i a e t
go ab an en d h zu ru th
dg le
sa s
ag yo az is u ba nd ou
eu is b is o o ro
n sw to m su su h m d ev
lk it ly ch
p
vo m
2. Calcule un intervalo de confianza para la media del precio ajustado a la inflación para cada marca.
Y
promedio_pre
NRO fabricante precio_inflacion cio fabricante promedio_precio
1 alfa-romero 33350 alfa-romero 38300.67
2 alfa-romero 40776 38300.666667 3
3 alfa-romero 40776
4 audi 34475 audi 44135.00
5 audi 43124 6
6 audi 37687 44135
7 audi 43766
8 audi 46756
9 audi 59002
10 bmw 40603 bmw 64546.13
11 bmw 41826 8
12 bmw 51822
13 bmw 52156 64546.125
14 bmw 60706
15 bmw 76016
16 bmw 102100
17 bmw 91140
18 chevrolet 12729 chevrolet 14844.67
19 chevrolet 15556 14844.666667 3
20 chevrolet 16249
21 dodge 13770 dodge 19251.50
22 dodge 15760 8
23 dodge 19664
24 dodge 15393 19251.5
25 dodge 16538
26 dodge 18804
27 dodge 22046
28 dodge 32037
29 honda 16011 honda 20226.46
30 honda 16940 13
31 honda 13342
32 honda 16135
33 honda 17618
34 honda 18028
35 honda 18028 20226.461538
36 honda 19511
37 honda 22476
38 honda 21858
39 honda 25441
40 honda 31991
41 honda 25565
42 isuzu 16767 22035 isuzu 22035.00
43 isuzu 27303 2
44 jaguar 79699 jaguar 85506.00
45 jaguar 87853 85506 3
46 jaguar 88966
47 mazda 12838 mazda 24346.83
48 mazda 15063 12
49 mazda 16792
50 mazda 16545
51 mazda 18275
52 mazda 21858 24346.833333
53 mazda 20993
54 mazda 26183
55 mazda 25318
56 mazda 27789
57 mazda 45175
58 mazda 45333
59 mercedes-benz 63146 mercedes-benz 83150.63
60 mercedes-benz 69808 8
61 mercedes-benz 69631
62 mercedes-benz 78092 83150.625
63 mercedes-benz 84478
64 mercedes-benz 86632
65 mercedes-benz 101223
66 mercedes-benz 112195
67 mercury 40783 40783 mercury 40783.00
68 mitsubishi 13318 mitsubishi 22833.77
69 mitsubishi 15294 13
70 mitsubishi 16481
71 mitsubishi 19001
72 mitsubishi 24612
73 mitsubishi 21003 22833.769231
74 mitsubishi 31210
75 mitsubishi 36745
76 mitsubishi 35806
77 mitsubishi 17272
78 mitsubishi 20237
79 mitsubishi 22930
80 mitsubishi 22930
81 nissan 13590 nissan 25739.83
82 nissan 17544 18
83 nissan 16431
84 nissan 16926
85 nissan 18161
86 nissan 18038
87 nissan 19274
88 nissan 18532
89 nissan 19767 25739.833333
90 nissan 20385
91 nissan 22115
92 nissan 23598
93 nissan 33359
94 nissan 35584
95 nissan 33359
96 nissan 42504
97 nissan 48681
98 nissan 45469
99 peugot 29408 peugot 38277.45
100 peugot 32621 11
101 peugot 30742
102 peugot 34252
103 peugot 38502
104 peugot 41764 38277.454545
105 peugot 41258
106 peugot 42196
107 peugot 41097
108 peugot 44359
109 peugot 44853
110 plymouth 13770 plymouth 19679.71
111 plymouth 19664 7
112 plymouth 15393
113 plymouth 16538 19679.714286
114 plymouth 18804
115 plymouth 22046
116 plymouth 31543
117 porsche 54412 porsche 77599.00
118 porsche 80386 4
119 porsche 84092 77599
120 porsche 91506
121 saab 29285 saab 37620.83
122 saab 30075 6
123 saab 37168 37620.833333
124 saab 38329
125 saab 44853
126 saab 46015
127 subaru 12648 subaru 21107.75
128 subaru 17430 12
129 subaru 18789
130 subaru 17610
131 subaru 19214
132 subaru 24614 21107.75
133 subaru 22817
134 subaru 27824
135 subaru 18443
136 subaru 25202
137 subaru 19803
138 subaru 28899
139 toyota 13217 toyota 24430.41
140 toyota 15663 32
141 toyota 16034
142 toyota 17096
143 toyota 19518
144 toyota 21692
145 toyota 17146
146 toyota 17788
147 toyota 19518
148 toyota 19246
149 toyota 19122
150 toyota 20655
151 toyota 22879
152 toyota 19913
153 toyota 20358
154 toyota 22978
155 toyota 23571 24430.40625
156 toyota 20879
157 toyota 23820
158 toyota 24685
159 toyota 27676
160 toyota 28541
161 toyota 43665
162 toyota 22113
163 toyota 26438
164 toyota 24683
165 toyota 26932
166 toyota 27796
167 toyota 40919
168 toyota 39535
169 toyota 38774
170 toyota 38923
171 volkswagen 19214 volkswagen 24904.33
172 volkswagen 19708 12
173 volkswagen 19758
174 volkswagen 20253
175 volkswagen 20993
176 volkswagen 23465 24904.333333
177 volkswagen 24701
178 volkswagen 28655
179 volkswagen 24663
180 volkswagen 32856
181 volkswagen 34214
182 volkswagen 30372
183 volvo 31978 volvo 44638.82
184 volvo 33152 11
185 volvo 39503
186 volvo 40812
187 volvo 45520 44638.818182
188 volvo 46831
189 volvo 41629
190 volvo 47066
191 volvo 53095
192 volvo 55529
193 volvo 55912
193
Varianza
𝑉=
153515197.52
14746560.02 21414.74
^
1410293527.52
707234187.52
4476045.44
505995.11 1522.52
1972152.11
30046842.25 Para muestras pequeñas n<30, menos el fabricante T
pequeñas.
12190572.25
170156.25
14888022.25 5432.97
7363082.25
200256.25
7809230.25 Tomamos el valor para la distribución normal a 2,5 %
163469010.25 Student (muestras menores a 30) se usa el 97,5%. D
17770115.98
10800829.44
-40000.00
0.00
1 2 3 4 5
-20000.00
57438714.69
59318236.69
41807000.69 -40000.00
51952861.36 10753.05
35674738.03
28674240.03
13139416.69
4587450.03
58051700.69
96907617.36
58051700.69
281037284.03
526297128.03
389240017.36
78667223.93
31995478.02
56783075.21
16204284.30
50420.66
12155999.21 5293.80
8883651.21
15354998.48
7949836.57
36985195.12
43237798.02
34924722.94
246.94
18375919.37
9870368.65 5480.81
766875.51
5599308.08
140737547.94
537636969.00
7767369.00 13972.90
42159049.00
193404649.00
69486117.36
56939600.69
205058.03 6453.66
501500.03
52304234.69
70462034.03
71567370.06
13525845.06
5376601.56
12234255.06
3586289.06
12293789.06 4590.60
2921535.56
45108014.06
7100892.56
16762883.06
1702372.56
60703576.56
125740479.73
76867412.35
70499637.92
53793515.04
24131735.17
7498868.79
53062574.42
44121560.79
24131735.17
26878068.17
28179176.92
14253692.35
2406861.35
20406959.23
16584492.67 7795.63
2109483.92
738579.10
12612486.35
372595.79
64817.98
10533878.79
16896980.98
369969596.73
5370371.73
4030432.67
63803.60
6257971.29
11327221.29
271873723.85
228148752.35
205738681.67
210035273.60
32379893.44
27001880.11
26484746.78
21634901.78
15298528.44
2071680.44 5154.55
41344.44
14067500.44
58241.78
63229002.78
86669893.44
29895378.78
160296317.03
131946991.94
26376628.40
14644537.40
776481.40 7810.16
4805661.12
9059005.49
5891211.58
71507010.94
118596060.03
127084628.31
193
32830.78238342
19938.40504517
=2.5%
0.95
Al despejar alfa, tomando en cuenta el 0.95 de nivel de confianza.
Por lo tanto 100%-2,5% =97.5%
ecio_inf - capac_motor
(𝑥_𝑖−𝑋 ̅) 〗 ^2 )/𝑛 〗
𝜎=√𝑣
equeñas n<30, menos el fabricante Toyota, se usa la fórmula para Districuión t de muestras
𝑡 𝑑𝑒 𝑆𝑡𝑢𝑑𝑒𝑛𝑡=
𝑥 ̅± 〖𝑡 _((𝛼/2,𝑛−1
or para la distribución normal a 2,5 %, por lo tanto para guiarnos en la tabla de Distribución de t
as menores a 30) se usa el 97,5%. De acuerdo a los grados de libertad de cada modelo.
precio
grados de libertad
Fabricante Cantidad Media Desviacion (n-1) t 97.5 student
alfa-romero 3 38300.67 3500.65 2 4.303 8696.79848
audi 6 44135.00 7788.32 5 2.571 8174.67404
bmw 8 64546.13 21414.74 7 2.365 17906.0142
chevrolet 3 14844.67 1522.52 2 4.303 3782.45222
dodge 8 19251.50 5432.97 7 2.365 4542.79707
honda 13 20226.46 4895.11 12 2.179 2958.33959
isuzu 2 22035.00 5268.00 1 12.706 47330.3395
jaguar 3 85506.00 4131.23 2 4.303 10263.38
mazda 12 24346.83 10333.16 11 2.201 6565.42378
mercedes-benz 8 83150.63 15694.94 7 2.365 13123.3827
mercury 1 40783.00 0 0
mitsubishi 13 22833.77 7225.05 12 2.179 4366.4273
nissan 18 25739.83 10753.05 17 2.11 5347.83436
peugot 11 38277.45 5293.80 10 2.228 3556.20425
plymouth 7 19679.71 5480.81 6 2.447 5069.08693
porsche 4 77599.00 13972.90 3 3.182 22230.8881
saab 6 37620.83 6453.66 5 2.571 6773.80499
subaru 12 21107.75 4590.60 11 2.201 2916.74847
toyota 32 24430.41 7795.63 31 2.042 2701.0496
volkswagen 12 24904.33 5154.55 11 2.201 3275.06877
volvo 11 44638.82 7810.16 10 2.228 5246.60968
193
0.00
0.00
0.00
0.00
0.00
0.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
0.00
0.00
0.00
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21
0.00
0.00
𝑆𝑡𝑢𝑑𝑒𝑛𝑡=
𝑡 _((𝛼/2,𝑛−1))∗𝑆/√𝑛 〗^
Intervalo
Mínimo Máximo
29603.87 46997.47
35960.33 52309.67
46640.11 82452.14
11062.21 18627.12
14708.70 23794.30
17268.12 23184.80
-25295.34 69365.34
75242.62 95769.38
17781.41 30912.26
70027.24 96274.01
18467.34 27200.20
20392.00 31087.67
34721.25 41833.66
14610.63 24748.80
55368.11 99829.89
30847.03 44394.64
18191.00 24024.50
21729.36 27131.46
21629.26 28179.40
39392.21 49885.43
19 20 21
19 20 21
3. Contraste la hipótesis, para un nivel de significación estadística del 99%, de que el precio de l
𝐹= 〖 (𝛼^2
𝑚𝑎𝑧𝑑𝑎)/(𝛼^2
106774289 5.0667
𝑠𝑢𝑏𝑎𝑟𝑢) 〗 ^ 21073618.7
Límites=(0.3679 ;2.718)
24346.83 1.153
21107.75
𝐹= 〖 (𝑢 𝑚𝑎𝑧𝑑𝑎−𝑢
𝑠𝑢𝑏𝑎𝑟𝑢)/(√((𝛼^2 𝑚𝑎𝑧𝑑𝑎)/𝑛_𝑚𝑎𝑧𝑑𝑎 +
24346.83-21107.75
(𝛼^2 𝑠𝑢𝑏𝑎𝑟𝑢)/𝑛_𝑠𝑢𝑏𝑎𝑟𝑢 ) ) 〗^
√(106774289/12+21073618.69/12)
106774289
12
𝑔.𝑙.= 〖 (106774289/12+21073618.69/12)^2/(1/
(12−1)∗(106774289/12)^2+1/(12−1)∗(21073618.69/12)^2 ) −2
〗^
𝑔.𝑙.= 〖 (8897857.411+1758.979167)^2/
(0.09090909∗(8897857.41)^2+0.9090909∗(1758.979167)^2 ) −2
〗^
4289/12+21073618.69/12)
24346.83-21107.75 3239.08 0.9923524176
21073618.6875 3264.0453895
12
𝑢𝑏𝑎𝑟𝑢
)^2 ) −2 〗
/
) −2
8897857.4144 1756134.8906
9/12)^2
0.0909090909
0909∗(1758.979167)^2 ) −2
1.135076E+14 15.18 13.18
7.477807E+12
4. Contraste la hipótesis, para un nivel de significación del 95%, de que el precio de los coches diésel de Merced
gasolina de la propia marca.
Diesel Gasolina
Mercedes Benz 4 4
Datos obtenidos
Mercedes Benz Diesel Gasolina
Media 70169.25 96132.00
n 4 4
Desviación 5303.68 11291.63 grados de libertad n-1
Varianza 28129055.687 127500991.5
Como las varianzas son diferentes, en muestras pequeñas, se usa la siguiente fórmula.
𝐹= 〖 (𝑢 𝑑𝑖𝑒𝑠𝑒𝑙−𝑢
𝑔𝑎𝑠𝑜𝑙𝑖𝑛𝑎)/(√((𝛼^2 𝑑𝑖𝑒𝑠𝑒𝑙)/𝑛_𝑑𝑖𝑒𝑠𝑒𝑙 +
70169.25 - 96132
(𝛼^2 𝑔𝑎𝑠𝑜𝑙𝑖𝑛𝑎)/𝑛_𝑔𝑎𝑠𝑜𝑙𝑖𝑛𝑎 ) ) 〗^
√(28129055.69/4+127500991.5/4)
𝐹= 〖 (𝑢 𝑑𝑖𝑒𝑠𝑒𝑙−𝑢
𝑔𝑎𝑠𝑜𝑙𝑖𝑛𝑎)/(√((𝛼^2 𝑑𝑖𝑒𝑠𝑒𝑙)/𝑛_𝑑𝑖𝑒𝑠𝑒𝑙 +
(𝛼^2 𝑔𝑎𝑠𝑜𝑙𝑖𝑛𝑎)/𝑛_𝑔𝑎𝑠𝑜𝑙𝑖𝑛𝑎 ) ) 〗^
Varianza
28129055.7
127500992
0.05
0.42498938
2 ) −2 0.3333333333
991.5
33∗(31875247.9 )^2 )
1.513794E+15 4.2622721 2.26
3.551614E+14
5. Desarrolle un modelo de regresión lineal que permita estimar la variable precio_inflacion a partir de las variables capacid
variables analizadas explica mejor el precio?
Se procede a usar el Análisis de Datos del utilitario Excel, para realizar la Regresión Lineal Múltiple, poniendo la varia
independientes (Longitud, peso, capacidad_motor y Capacidad_pontencia
193
de las variables capacidad_motor, caballos_potencia, longitud y peso. ¿Cuál de las
Y
precio_inflacion Coeficientes
33350 Intercepción -24993.5109626519
40776 Variable X 1 -64.0712501490219
40776 Variable X 2 21.4983610266806
34475 Variable X 3 -2565.61687373519
43124 Variable X 4 215.117080726653
37687
43766
46756
59002
40603
𝑦 ̂=𝑏_0+𝑏_1 𝑥_1+𝑏_2
41826
𝑦 ̂=−24993.51+(−64.07𝑥_1 )+21.50𝑥_2
60706
+215.12𝑥_4
76016
102100
91140
12729 Al establecer la ecuación de regresión, podemos ver una ecuación co
Caballos_potencia, Capacidad_motor, Longitud y Peso. Al cambiar su
15556 Caballos_Potencia, tomando en cuenta sus Coeficientes.
16249
13770 La que más provoca una variación en los precios_inflación son los ca
15760
19664
15393
16538
18804
22046
32037
16011
16940
13342 Precio con realcion
16135
120000
17618
18028
18028
19511 100000
f(x) = 427.848024088587 x − 11443.729
22476 R² = 0.660080658733501
21858
25441 80000
31991
25565
16767 60000
27303
79699
87853
40000
88966
12838
15063
16792 20000
16545
18275
21858 0
0 50 100
20993
26183
25318
27789 Precio con relacio
45175
45333 120000
63146
69808
100000
69631
78092
84478
80000
86632
101223
112195
60000
40783
13318
15294
40000
16481 f(x) = 6084.49451256712 x + 1306
R² = 0.00921707461310295
20000
40000
f(x) = 6084.49451256712 x + 1306
19001 R² = 0.00921707461310295
24612
20000
21003
31210
36745
0
35806 1.5 2 2.5
17272
20237
22930 Precio en
22930
120000
13590
17544
16431
100000
16926
18161
18038
80000
19274 f(x) = 31.7053357917446 x − 48382.681
R² = 0.697837792585694
18532
19767 60000
20385
22115
23598 40000
33359
35584
33359 20000
42504
48681
45469 0
1000 1500 2000 2500
29408
32621
30742
34252 Precio en r
38502 120000
41764
41258
42196 100000
41097
44359
44853 80000
13770
f(x) = 1114.84987039499 x − 161517
19664 R² = 0.484314106460039
60000
15393
16538
18804 40000
22046
20000
40000
31543
54412 20000
80386
84092
91506 0
130 140 150 160 1
29285
30075
37168
38329
44853
46015
12648
17430
18789
17610
19214
24614
22817
27824
18443
25202
19803
28899
13217
15663
16034
17096
19518
21692
17146
17788
19518
19246
19122
20655
22879
19913
20358
22978
23571
20879
23820
24685
27676
28541
43665
22113
26438
24683
26932
27796
40919
39535
38774
38923
19214
19708
19758
20253
20993
23465
24701
28655
24663
32856
34214
30372
31978
33152
39503
40812
45520
46831
41629
47066
53095
55529
55912
𝑏_2
𝑥_4
07𝑥_1 )+21.50𝑥_2+(−2565.62𝑥_3 )
sión, podemos ver una ecuación con predicciones de acuerdo a la variación del precio en cuanto a
otor, Longitud y Peso. Al cambiar sus valores, el precio varía, por lo tanto la variable que más cambia el precio es
uenta sus Coeficientes.
Estadísticas de la regresión
Coeficiente de correlación múltiple 0.87939853
Coeficiente de determinación R^2 0.77334178
R^2 ajustado 0.76851926
Error típico 9617.80312
Observaciones 193
ANÁLISIS DE VARIANZA
Grados de Suma de Promedio de los
libertad cuadrados cuadrados F
Regresión 4 5.9335E+10 14833704366.312 160.360667
Residuos 188 1.739E+10 92502136.77454
Total 192 7.6725E+10
A medida que sube los Caballos_potencia, el precio se incrementa, por lo tanto la relación entre el
Precio_inflación y Caballos_potencia es más proporcional.
Valor crítico de F
1.8721975258E-59
3.4 43124
100000
3.4 37687
3.4 43766 80000
3.4 46756
3.4 59002 60000
2.8 40603
2.8 41826 40000
f(x) = 6084.49451256712 x + 13063.1109108033
3.19 51822 R² = 0.00921707461310295
20000
3.19 52156
3.19 60706 0
3.39 76016 1.5 2 2.5 3 3.5
3.39 102100
3.39 91140
3.03 12729
3.11 15556
3.11 16249
3.23 13770
3.23 15760
3.39 19664
3.23 15393
3.23 16538
3.23 18804
3.46 22046
3.9 32037
3.41 16011
3.41 16940
3.07 13342
3.41 16135
3.41 17618
3.41 18028
3.41 18028
3.58 19511
3.58 22476
3.58 21858
3.58 25441
3.58 31991
3.58 25565
3.23 16767
3.23 27303
4.17 79699
4.17 87853
2.76 88966
3.15 12838
3.15 15063
3.15 16792
3.15 16545
3.15 18275
3.39 21858
3.39 20993
3.39 26183
3.39 25318
3.39 27789
3.16 45175
3.64 45333
3.64 63146
3.64 69808
3.64 69631
3.64 78092
3.1 84478
3.1 86632
3.35 101223
3.35 112195
3.12 40783
3.23 13318
3.23 15294
3.23 16481
3.39 19001
3.46 24612
3.46 21003
3.86 31210
3.86 36745
3.86 35806
3.46 17272
3.46 20237
3.46 22930
3.46 22930
3.29 13590
3.47 17544
3.29 16431
3.29 16926
3.29 18161
3.29 18038
3.29 19274
3.29 18532
3.29 19767
3.29 20385
3.47 22115
3.47 23598
3.27 33359
3.27 35584
3.27 33359
3.27 42504
3.27 48681
3.27 45469
3.19 29408
3.52 32621
3.19 30742
3.52 34252
2.19 38502
3.52 41764
2.19 41258
3.52 42196
3.19 41097
3.52 44359
3.21 44853
3.23 13770
3.39 19664
3.23 15393
3.23 16538
3.23 18804
3.46 22046
3.86 31543
3.11 54412
2.9 80386
2.9 84092
2.9 91506
3.07 29285
3.07 30075
2.07 37168
3.07 38329
3.07 44853
3.07 46015
2.36 12648
2.64 17430
2.64 18789
2.64 17610
2.64 19214
2.64 24614
2.64 22817
2.64 27824
2.64 18443
2.64 25202
2.64 19803
2.64 28899
3.03 13217
3.03 15663
3.03 16034
3.03 17096
3.03 19518
3.03 21692
3.03 17146
3.03 17788
3.35 19518
3.35 19246
3.03 19122
3.03 20655
3.03 22879
3.03 19913
3.03 20358
3.08 22978
3.08 23571
3.5 20879
3.5 23820
3.5 24685
3.5 27676
3.5 28541
3.5 43665
3.54 22113
3.35 26438
3.54 24683
3.54 26932
3.54 27796
3.35 40919
3.35 39535
3.35 38774
3.35 38923
3.4 19214
3.4 19708
3.4 19758
3.4 20253
3.4 20993
3.4 23465
3.4 24701
3.4 28655
3.4 24663
3.4 32856
3.4 34214
3.4 30372
3.15 31978
3.15 33152
3.15 39503
3.15 40812
3.15 45520
3.15 46831
3.15 41629
3.15 47066
2.87 53095
3.4 55529
3.15 55912
acion a Capacidad de Motor
4.49451256712 x + 13063.1109108033
21707461310295
5 3 3.5 4 4.5
peso precio_inflacion
2548 33350
2548 40776
2823 40776
2337 34475
2824 43124
2507 37687
2844 43766
2954 46756
3086 59002
2395 40603
2395 41826
2710 51822
2765 52156
3055 60706
3230 76016
3380 102100
3505 91140
1488 12729
1874 15556
1909 16249
1876 13770
1876 15760
2128 19664
1967 15393
1989 16538
1989 18804
2535 22046
2811 32037
1713 16011
1819 16940
1837 13342
1940 16135
1956 17618
2010 18028
2024 18028
2236 19511
2289 22476
2304 21858
2372 25441
2465 31991
2293 25565
2337 16767
2734 27303
4066 79699
4066 87853
3950 88966
1890 12838
1900 15063
1905 16792
1945 16545
1950 18275
2385 21858
2410 20993
2385 26183
2410 25318
2425 27789
2670 45175
2700 45333
3515 63146
3750 69808
3495 69631
3770 78092
3740 84478
3685 86632
3900 101223
3715 112195
2910 40783
1918 13318
1944 15294
2004 16481
2145 19001
2370 24612
2328 21003
2833 31210
2921 36745
2926 35806
2365 17272
2405 20237
2403 22930
2403 22930
1889 13590
2017 17544
1918 16431
1938 16926
2024 18161
1951 18038
2028 19274
1971 18532
2037 19767
2008 20385
2324 22115
2302 23598
3095 33359
3296 35584
3060 33359
3071 42504
3139 48681
3139 45469
3020 29408
3197 32621
3230 30742
3430 34252
3075 38502
3252 41764
3285 41258
3485 42196
3075 41097
3252 44359
3130 44853
1918 13770
2128 19664
1967 15393
1989 16538
2191 18804
2535 22046
2818 31543
2778 54412
2756 80386
2756 84092
2800 91506
2658 29285
2695 30075
2707 37168
2758 38329
2808 44853
2847 46015
2050 12648
2120 17430
2240 18789
2145 17610
2190 19214
2340 24614
2385 22817
2510 27824
2290 18443
2455 25202
2420 19803
2650 28899
1985 13217
2040 15663
2015 16034
2280 17096
2290 19518
3110 21692
2081 17146
2109 17788
2275 19518
2275 19246
2094 19122
2122 20655
2140 22879
2169 19913
2204 20358
2265 22978
2300 23571
2540 20879
2536 23820
2551 24685
2679 27676
2714 28541
2975 43665
2326 22113
2480 26438
2414 24683
2414 26932
2458 27796
2976 40919
3016 39535
3131 38774
3151 38923
2261 19214
2209 19708
2264 19758
2212 20253
2275 20993
2319 23465
2300 24701
3049 47066
0
3012 53095 1000 1500 2000 2500 3000
3217 55529
3062 55912
Precio en relacion a Peso
Precio en relacion a Peso
= 31.7053357917446 x − 48382.6816616609
= 0.697837792585694
188.8 55912
0
130 140 150 160 170 180 19
recio en relación a Longitud
x) = 1114.84987039499 x − 161517.009789841
= 0.484314106460039