75:@0.902994:0.967780:0.920058:0.967780:0.920058:0.951792:0.902994:0.951792:0.000000:0.000000
Mediana:@0.096359:0.074294:0.179945:0.074294:0.179945:0.053523:0.096359:0.053523:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
La mediana es el valor medio de una secuencia de datos. Es el valor que divide :@0.096359:0.096352:0.627383:0.096352:0.627383:0.080572:0.096359:0.080572:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
a la secuencia en dos partes numéricamente iguales.:@0.096359:0.112948:0.449169:0.112948:0.449169:0.097168:0.096359:0.097168:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
Para entender mejor esta medida de tendencia central, tomemos el ejem-:@0.096359:0.136667:0.623384:0.136667:0.623384:0.120887:0.096359:0.120887:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
plo de las 39 estudiantes del primer curso de bachillerato mencionadas en la :@0.096359:0.153264:0.627466:0.153264:0.627466:0.137483:0.096359:0.137483:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
 :@0.623463:0.153264:0.627425:0.153264:0.627425:0.137483:0.623463:0.137483:0.000000
página anterior. Los pesos de cada una, ordenados de menor a mayor, son los :@0.096359:0.169860:0.627473:0.169860:0.627473:0.154080:0.096359:0.154080:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
siguientes::@0.096359:0.186456:0.165573:0.186456:0.165573:0.170676:0.096359:0.170676:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
N° de estudiante:@0.185177:0.215457:0.288135:0.215457:0.288135:0.201112:0.185177:0.201112:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
1:@0.393074:0.215457:0.400462:0.215457:0.400462:0.201112:0.393074:0.201112:0.000000
2:@0.433565:0.215457:0.440952:0.215457:0.440952:0.201112:0.433565:0.201112:0.000000
3:@0.474055:0.215457:0.481443:0.215457:0.481443:0.201112:0.474055:0.201112:0.000000
4:@0.514546:0.215457:0.521933:0.215457:0.521933:0.201112:0.514546:0.201112:0.000000
5:@0.555036:0.215457:0.562424:0.215457:0.562424:0.201112:0.555036:0.201112:0.000000
6:@0.595527:0.215457:0.602915:0.215457:0.602915:0.201112:0.595527:0.201112:0.000000
7:@0.636570:0.215457:0.643958:0.215457:0.643958:0.201112:0.636570:0.201112:0.000000
8:@0.677614:0.215457:0.685001:0.215457:0.685001:0.201112:0.677614:0.201112:0.000000
9:@0.718104:0.215457:0.725492:0.215457:0.725492:0.201112:0.718104:0.201112:0.000000
10:@0.754892:0.215457:0.769668:0.215457:0.769668:0.201112:0.754892:0.201112:0.000000:0.000000
11:@0.795383:0.215457:0.810158:0.215457:0.810158:0.201112:0.795383:0.201112:0.000000:0.000000
12:@0.835873:0.215457:0.850649:0.215457:0.850649:0.201112:0.835873:0.201112:0.000000:0.000000
13:@0.876364:0.215457:0.891140:0.215457:0.891140:0.201112:0.876364:0.201112:0.000000:0.000000
Peso:@0.222484:0.243860:0.250962:0.243860:0.250962:0.229514:0.222484:0.229514:0.000000:0.000000:0.000000:0.000000
42:@0.389456:0.243860:0.404231:0.243860:0.404231:0.229514:0.389456:0.229514:0.000000:0.000000
43:@0.429946:0.243860:0.444722:0.243860:0.444722:0.229514:0.429946:0.229514:0.000000:0.000000
43:@0.470437:0.243860:0.485212:0.243860:0.485212:0.229514:0.470437:0.229514:0.000000:0.000000
44:@0.510927:0.243860:0.525703:0.243860:0.525703:0.229514:0.510927:0.229514:0.000000:0.000000
44:@0.551418:0.243860:0.566193:0.243860:0.566193:0.229514:0.551418:0.229514:0.000000:0.000000
44:@0.591908:0.243860:0.606684:0.243860:0.606684:0.229514:0.591908:0.229514:0.000000:0.000000
45:@0.632952:0.243860:0.647727:0.243860:0.647727:0.229514:0.632952:0.229514:0.000000:0.000000
45:@0.673995:0.243860:0.688771:0.243860:0.688771:0.229514:0.673995:0.229514:0.000000:0.000000
45:@0.714486:0.243860:0.729261:0.243860:0.729261:0.229514:0.714486:0.229514:0.000000:0.000000
45:@0.754976:0.243860:0.769752:0.243860:0.769752:0.229514:0.754976:0.229514:0.000000:0.000000
45:@0.795467:0.243860:0.810242:0.243860:0.810242:0.229514:0.795467:0.229514:0.000000:0.000000
46:@0.835957:0.243860:0.850733:0.243860:0.850733:0.229514:0.835957:0.229514:0.000000:0.000000
46:@0.876448:0.243860:0.891223:0.243860:0.891223:0.229514:0.876448:0.229514:0.000000:0.000000
N° de estudiante:@0.185328:0.272262:0.288286:0.272262:0.288286:0.257916:0.185328:0.257916:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
14:@0.389539:0.272262:0.404315:0.272262:0.404315:0.257916:0.389539:0.257916:0.000000:0.000000
15:@0.430030:0.272262:0.444805:0.272262:0.444805:0.257916:0.430030:0.257916:0.000000:0.000000
16:@0.470520:0.272262:0.485296:0.272262:0.485296:0.257916:0.470520:0.257916:0.000000:0.000000
17:@0.511011:0.272262:0.525787:0.272262:0.525787:0.257916:0.511011:0.257916:0.000000:0.000000
18:@0.551501:0.272262:0.566277:0.272262:0.566277:0.257916:0.551501:0.257916:0.000000:0.000000
19:@0.591992:0.272262:0.606768:0.272262:0.606768:0.257916:0.591992:0.257916:0.000000:0.000000
20:@0.633035:0.272262:0.647811:0.272262:0.647811:0.257916:0.633035:0.257916:0.000000:0.000000
21:@0.674079:0.272262:0.688854:0.272262:0.688854:0.257916:0.674079:0.257916:0.000000:0.000000
22:@0.714569:0.272262:0.729345:0.272262:0.729345:0.257916:0.714569:0.257916:0.000000:0.000000
23:@0.755060:0.272262:0.769835:0.272262:0.769835:0.257916:0.755060:0.257916:0.000000:0.000000
24:@0.795550:0.272262:0.810326:0.272262:0.810326:0.257916:0.795550:0.257916:0.000000:0.000000
25:@0.836041:0.272262:0.850817:0.272262:0.850817:0.257916:0.836041:0.257916:0.000000:0.000000
26:@0.876531:0.272262:0.891307:0.272262:0.891307:0.257916:0.876531:0.257916:0.000000:0.000000
Peso:@0.222652:0.300665:0.251129:0.300665:0.251129:0.286319:0.222652:0.286319:0.000000:0.000000:0.000000:0.000000
46:@0.389623:0.300665:0.404399:0.300665:0.404399:0.286319:0.389623:0.286319:0.000000:0.000000
46:@0.430114:0.300665:0.444889:0.300665:0.444889:0.286319:0.430114:0.286319:0.000000:0.000000
46:@0.470604:0.300665:0.485380:0.300665:0.485380:0.286319:0.470604:0.286319:0.000000:0.000000
47:@0.511095:0.300665:0.525870:0.300665:0.525870:0.286319:0.511095:0.286319:0.000000:0.000000
47:@0.551585:0.300665:0.566361:0.300665:0.566361:0.286319:0.551585:0.286319:0.000000:0.000000
48:@0.592076:0.300665:0.606851:0.300665:0.606851:0.286319:0.592076:0.286319:0.000000:0.000000
48:@0.633119:0.300665:0.647895:0.300665:0.647895:0.286319:0.633119:0.286319:0.000000:0.000000
48:@0.674163:0.300665:0.688938:0.300665:0.688938:0.286319:0.674163:0.286319:0.000000:0.000000
48:@0.714653:0.300665:0.729429:0.300665:0.729429:0.286319:0.714653:0.286319:0.000000:0.000000
48:@0.755144:0.300665:0.769919:0.300665:0.769919:0.286319:0.755144:0.286319:0.000000:0.000000
49:@0.795634:0.300665:0.810410:0.300665:0.810410:0.286319:0.795634:0.286319:0.000000:0.000000
49:@0.836125:0.300665:0.850900:0.300665:0.850900:0.286319:0.836125:0.286319:0.000000:0.000000
49:@0.876615:0.300665:0.891391:0.300665:0.891391:0.286319:0.876615:0.286319:0.000000:0.000000
N° de estudiante:@0.185495:0.329067:0.288454:0.329067:0.288454:0.314721:0.185495:0.314721:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
27:@0.389707:0.329067:0.404482:0.329067:0.404482:0.314721:0.389707:0.314721:0.000000:0.000000
28:@0.430197:0.329067:0.444973:0.329067:0.444973:0.314721:0.430197:0.314721:0.000000:0.000000
29:@0.470688:0.329067:0.485464:0.329067:0.485464:0.314721:0.470688:0.314721:0.000000:0.000000
30:@0.511178:0.329067:0.525954:0.329067:0.525954:0.314721:0.511178:0.314721:0.000000:0.000000
31:@0.551669:0.329067:0.566445:0.329067:0.566445:0.314721:0.551669:0.314721:0.000000:0.000000
32:@0.592160:0.329067:0.606935:0.329067:0.606935:0.314721:0.592160:0.314721:0.000000:0.000000
33:@0.633203:0.329067:0.647979:0.329067:0.647979:0.314721:0.633203:0.314721:0.000000:0.000000
34:@0.674246:0.329067:0.689022:0.329067:0.689022:0.314721:0.674246:0.314721:0.000000:0.000000
35:@0.714737:0.329067:0.729512:0.329067:0.729512:0.314721:0.714737:0.314721:0.000000:0.000000
36:@0.755227:0.329067:0.770003:0.329067:0.770003:0.314721:0.755227:0.314721:0.000000:0.000000
37:@0.795718:0.329067:0.810494:0.329067:0.810494:0.314721:0.795718:0.314721:0.000000:0.000000
38:@0.836208:0.329067:0.850984:0.329067:0.850984:0.314721:0.836208:0.314721:0.000000:0.000000
39:@0.876699:0.329067:0.891475:0.329067:0.891475:0.314721:0.876699:0.314721:0.000000:0.000000
Peso:@0.222819:0.357470:0.251297:0.357470:0.251297:0.343124:0.222819:0.343124:0.000000:0.000000:0.000000:0.000000
50:@0.389791:0.357470:0.404566:0.357470:0.404566:0.343124:0.389791:0.343124:0.000000:0.000000
50:@0.430281:0.357470:0.445057:0.357470:0.445057:0.343124:0.430281:0.343124:0.000000:0.000000
50:@0.470772:0.357470:0.485547:0.357470:0.485547:0.343124:0.470772:0.343124:0.000000:0.000000
50:@0.511262:0.357470:0.526038:0.357470:0.526038:0.343124:0.511262:0.343124:0.000000:0.000000
51:@0.551753:0.357470:0.566528:0.357470:0.566528:0.343124:0.551753:0.343124:0.000000:0.000000
51:@0.592243:0.357470:0.607019:0.357470:0.607019:0.343124:0.592243:0.343124:0.000000:0.000000
51:@0.633287:0.357470:0.648062:0.357470:0.648062:0.343124:0.633287:0.343124:0.000000:0.000000
51:@0.674330:0.357470:0.689106:0.357470:0.689106:0.343124:0.674330:0.343124:0.000000:0.000000
52:@0.714821:0.357470:0.729596:0.357470:0.729596:0.343124:0.714821:0.343124:0.000000:0.000000
53:@0.755311:0.357470:0.770087:0.357470:0.770087:0.343124:0.755311:0.343124:0.000000:0.000000
54:@0.795802:0.357470:0.810577:0.357470:0.810577:0.343124:0.795802:0.343124:0.000000:0.000000
54:@0.836292:0.357470:0.851068:0.357470:0.851068:0.343124:0.836292:0.343124:0.000000:0.000000
55:@0.876783:0.357470:0.891558:0.357470:0.891558:0.343124:0.876783:0.343124:0.000000:0.000000
Existen 39 mediciones. Por lo tanto, en la medición 20, se divide exactamente :@0.096359:0.391153:0.627385:0.391153:0.627385:0.375372:0.096359:0.375372:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
por la mitad a la secuencia de datos, ya que existen 19 mediciones antes y 19 :@0.096359:0.407749:0.627370:0.407749:0.627370:0.391969:0.096359:0.391969:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
mediciones después.:@0.096359:0.424345:0.236905:0.424345:0.236905:0.408565:0.096359:0.408565:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
¿Cuándo utilizar el promedio :@0.096359:0.454262:0.379200:0.454262:0.379200:0.433491:0.096359:0.433491:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
y cuándo utilizar la mediana? :@0.096359:0.475384:0.380513:0.475384:0.380513:0.454614:0.096359:0.454614:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
La respuesta tendrá que ver con los da-:@0.096359:0.497444:0.383607:0.497444:0.383607:0.481663:0.096359:0.481663:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
tos recabados. Si los datos son bastante  :@0.096359:0.514040:0.387626:0.514040:0.387626:0.498260:0.096359:0.498260:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
homogéneos (como es el análisis de los pe-:@0.096359:0.530636:0.383663:0.530636:0.383663:0.514856:0.096359:0.514856:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
sos), se utiliza el promedio. Pero si existen :@0.096359:0.547233:0.387626:0.547233:0.387626:0.531452:0.096359:0.531452:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
 :@0.383664:0.547233:0.387626:0.547233:0.387626:0.531452:0.383664:0.531452:0.000000
datos extremos en una serie, tanto ha-:@0.096359:0.563829:0.383664:0.563829:0.383664:0.548049:0.096359:0.548049:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
cia abajo como hacia arriba, es prudente :@0.096359:0.580425:0.387643:0.580425:0.387643:0.564645:0.096359:0.564645:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
utilizar la mediana ya que esta elimina los  :@0.096359:0.597022:0.387626:0.597022:0.387626:0.581241:0.096359:0.581241:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
efectos de los extremos. Por ejemplo, ¿qué :@0.096359:0.613618:0.387602:0.613618:0.387602:0.597838:0.096359:0.597838:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
pasaría si existieran dos personas con pesos  :@0.096359:0.630215:0.387626:0.630215:0.387626:0.614434:0.096359:0.614434:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
superiores a 100 kilos? En este caso, el pro-:@0.096359:0.646811:0.383699:0.646811:0.383699:0.631031:0.096359:0.631031:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
medio  se  incrementaría sustancialmente :@0.096359:0.663407:0.387626:0.663407:0.387626:0.647627:0.096359:0.647627:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
 :@0.383664:0.663407:0.387626:0.663407:0.387626:0.647627:0.383664:0.647627:0.000000
y las conclusiones derivadas de este análisis :@0.096359:0.680004:0.387641:0.680004:0.387641:0.664223:0.096359:0.664223:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
podrían ser erróneas. Al utilizar la mediana,  :@0.096359:0.696600:0.387626:0.696600:0.387626:0.680820:0.096359:0.680820:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
la existencia de dos datos extremos no :@0.096359:0.713196:0.387569:0.713196:0.387569:0.697416:0.096359:0.697416:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
afecta el resultado final.:@0.096359:0.729793:0.255590:0.729793:0.255590:0.714012:0.096359:0.714012:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
En el uso de la mediana pueden darse dos situaciones::@0.096359:0.753512:0.463082:0.753512:0.463082:0.737731:0.096359:0.737731:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
1.:@0.096359:0.777438:0.108098:0.777438:0.108098:0.761450:0.096359:0.761450:0.000000:0.000000
 Si el tamaño de la muestra es un número impar, la mediana sería el dato :@0.108098:0.777231:0.627313:0.777231:0.627313:0.761450:0.108098:0.761450:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
  que separe en partes iguales a la serie. Para obtener este dato, la fórmula es la  :@0.096359:0.793827:0.627425:0.793827:0.627425:0.778047:0.096359:0.778047:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
  siguiente: (n+1) / 2.:@0.096359:0.810424:0.240426:0.810424:0.240426:0.794643:0.096359:0.794643:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
2.:@0.096359:0.834350:0.108098:0.834350:0.108098:0.818362:0.096359:0.818362:0.000000:0.000000
 Si el tamaño de la muestra es un número par, entonces la mediana será  :@0.108098:0.834143:0.627425:0.834143:0.627425:0.818362:0.108098:0.818362:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
  el valor promedio entre los dos datos que dividen la serie. Por ejemplo, si se :@0.096359:0.850739:0.627401:0.850739:0.627401:0.834958:0.096359:0.834958:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
  tienen los siguientes diez datos::@0.096359:0.867335:0.321615:0.867335:0.321615:0.851555:0.096359:0.851555:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
 :@0.096359:0.934260:0.100321:0.934260:0.100321:0.918479:0.096359:0.918479:0.000000
1:@0.131531:0.896745:0.139890:0.896745:0.139890:0.881909:0.131531:0.881909:0.000000
2:@0.182592:0.896745:0.190951:0.896745:0.190951:0.881909:0.182592:0.881909:0.000000
3:@0.233653:0.896745:0.242013:0.896745:0.242013:0.881909:0.233653:0.881909:0.000000
4:@0.284715:0.896745:0.293074:0.896745:0.293074:0.881909:0.284715:0.881909:0.000000
5:@0.336077:0.896430:0.343834:0.896430:0.343834:0.881896:0.336077:0.881896:0.000000
6:@0.387139:0.896430:0.394895:0.896430:0.394895:0.881896:0.387139:0.881896:0.000000
7:@0.438602:0.896745:0.446961:0.896745:0.446961:0.881909:0.438602:0.881909:0.000000
8:@0.490367:0.896745:0.498726:0.896745:0.498726:0.881909:0.490367:0.881909:0.000000
9:@0.541428:0.896745:0.549788:0.896745:0.549788:0.881909:0.541428:0.881909:0.000000
10:@0.588301:0.896745:0.605020:0.896745:0.605020:0.881909:0.588301:0.881909:0.000000:0.000000
38:@0.128314:0.924443:0.143090:0.924443:0.143090:0.910097:0.128314:0.910097:0.000000:0.000000
39:@0.179375:0.924443:0.194151:0.924443:0.194151:0.910097:0.179375:0.910097:0.000000:0.000000
43:@0.230437:0.924443:0.245212:0.924443:0.245212:0.910097:0.230437:0.910097:0.000000:0.000000
45:@0.281498:0.924443:0.296274:0.924443:0.296274:0.910097:0.281498:0.910097:0.000000:0.000000
46:@0.332559:0.924443:0.347335:0.924443:0.347335:0.910097:0.332559:0.910097:0.000000:0.000000
48:@0.383621:0.924443:0.398396:0.924443:0.398396:0.910097:0.383621:0.910097:0.000000:0.000000
50:@0.435386:0.924443:0.450161:0.924443:0.450161:0.910097:0.435386:0.910097:0.000000:0.000000
51:@0.487150:0.924443:0.501926:0.924443:0.501926:0.910097:0.487150:0.910097:0.000000:0.000000
53:@0.538212:0.924443:0.552987:0.924443:0.552987:0.910097:0.538212:0.910097:0.000000:0.000000
55:@0.589273:0.924443:0.604049:0.924443:0.604049:0.910097:0.589273:0.910097:0.000000:0.000000
La mediana sería el promedio entre el dato 5 (46) y el dato 6 (48). En conse-:@0.096359:0.957994:0.623491:0.957994:0.623491:0.942213:0.096359:0.942213:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
cuencia, la mediana es 47.:@0.096359:0.974590:0.270111:0.974590:0.270111:0.958810:0.096359:0.958810:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
 En las competencias deportivas de velocidad, no importa tanto la mediana, sino la más rápida.:@0.424646:0.722284:0.892889:0.722284:0.892889:0.710808:0.424646:0.710808:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
Shutterstock, 1397216249:@0.921317:0.704746:0.921317:0.629738:0.909698:0.629738:0.909698:0.704746:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
Cálculo de mediana.:@0.667880:0.134838:0.793823:0.134838:0.793823:0.120492:0.667880:0.120492:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
lynk.ec/12e16:@0.667880:0.153798:0.754758:0.153798:0.754758:0.139213:0.667880:0.139213:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
Competencia digital:@0.657894:0.115409:0.794669:0.115409:0.794669:0.093079:0.657894:0.093079:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000
 ©:@0.079553:0.731952:0.079553:0.720342:0.061505:0.720342:0.061505:0.731952:0.000000:0.000000
maya:@0.080774:0.720340:0.080774:0.684191:0.055786:0.684191:0.055786:0.720340:0.000000:0.000000:0.000000:0.000000
®EDUCACIÓN – Libro resuelto solo para fines didácticos – Prohibida su reproducción :@0.079553:0.684191:0.079553:0.268044:0.061505:0.268044:0.061505:0.684191:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000:0.000000