Analisis Bivariado
Marco Javier Peñaloza Pérez
2023-03-20
data =read_excel("data_proyecto_ciencia_datos(agrupada3).xlsx", sheet = "data",na = "-")
head(data)| ID | NOM_SEDE | NOM_JORNADA | NOM_MODALIDAD | NOM_EST_METODOLOGICA | v1 | v2 | v3 | v4 | v5 | v6 | v7 | v8 | v9 | v10 | v11 | v12 | v13 | v14 | v15 | v16 | v17 | v18 | v19 | v20 | v21 | v22 | v23 | v24 | v25 | v26 | v27 | v28 | v29 | v30 | v31 | v32 | v33 | v34 | v35 | v36 | v37 | v38 | v39 | v40 | v41 | v42 | v43 | v44 | v45 | v46 | v47 | v48 | v49 | v50 | v51 | v52 | v53 | v54 | v55 | v56 | v57 | v58 | v59 | v60 | v61 | v62 | v63 | v64 | v65 | v66 | v67 | v68 | v69 | v70 | v71 | v72 | v73 | v74 | v75 | v76 | v77 | v78 | v79 | v80 | v81 | v82 | v83 | v84 | v85 | NOMBRE PROGRAMA | PROMEDIO GENERAL | ULTIMO SEMESTRE CURSADO | MAXIMO PERIODO CURSADO | TOTAL APROBADAS | TOTAL REPROBADAS | TOTAL INCENTIVOS | MAX SEMESTRE INCENTIVO | PROMEDIO INCENTIVO | MAX SEMESTRE CREDITO | PROMEDIO CREDITO | PROMEDIO CUOTA INICIAL | MAX PERIODO DE DESERCION | DESERTOR |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 128095 | SINCELEJO | JORNADA DIURNA | Pregrado | Presencial | Beca o Auxilio de Bienestar Institucional | ninguna | NA | NA | Usted | Cónyuge o esposa(o) | NA | NA | NA | Colombia - Sucre - Sincelejo | NA | NA | NA | otros | NA | NA | Hermeneutica | Café Salud | 34 | Entre 31 y 49 años | $3.000.001 o más | NA | NA | NA | NA | NA | NA | CASADO | Estrato Dos | Si | NA | NA | NA | Masculino | $3.000.001 o más | NA | 5 o más | NA | NA | 1 | NA | NA | Secundaria | Universitario | NA | 5 o más | 1 | 3 | 2 | Empleado | NA | Otros | NA | No | No | Si | Diestro | NA | No | NA | No | NA | Otro | NA | NA | Educación | NA | Indefinido | No aplica | NA | NA | Empleado | NA | NA | Talento excepcional general | NA | NA | Si | Si | No | Otra | Familiar | NA | NA | NA | INGENIERIA DE SISTEMAS | 4.966667 | 2 | 20182 | 26 | 0 | 2 | 2 | 2021955 | NA | NA | NA | 20192 | 1 |
| 4101 | SINCELEJO | JORNADA DIURNA | Pregrado | Presencial | NA | NA | NA | NA | NA | NA | NA | NA | NA | Colombia - Bolivar - Magangue | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | INGENIERIA INDUSTRIAL | 4.525000 | 10 | 20172 | 10 | 0 | 3 | 10 | 1405600 | NA | NA | NA | NA | 0 |
| 112830 | SINCELEJO | JORNADA DIURNA | Pregrado | Presencial | Crédito Icetex | ninguna | NA | NA | Otro | Otro | NA | Menos de 1 año | NA | NA | NA | NA | NA | NA | NA | NA | NA | AMBUR EPS | 18 | Entre 20 y 30 años | Entre $1.000.000 y $1.599.999 | Estudiante | NA | NA | NA | NA | NA | SOLTERO | Estrato Uno | Si | NA | NA | NA | Femenino | Entre $100.000 y 699.999 | NA | 1 | NA | NA | 1 | NA | Universitario | Ninguno | NA | NA | 1 | NA | 4 | 1 | Estudiante | Amigo(a) o Conocido(a) | Indigena | NA | Si | No | Si | Diestro | NA | Si | NA | No | NA | NA | NA | Otro | NA | NA | NA | Viaja cada vez que tiene programado clases o tutorias presenciales | NA | Hogar | NA | NA | NA | No aplica | NA | NA | Si | No | No | Pensión | Propia | NA | NA | NA | INGENIERIA INDUSTRIAL | 4.445000 | 10 | 20212 | 110 | 0 | 1 | 4 | 3322100 | NA | NA | NA | NA | 0 |
| 17884 | SINCELEJO | JORNADA DIURNA | Pregrado | Presencial | Crédito Icetex | Ninguna otra por el momento | NA | NA | NA | NA | Menos de 1 año | NA | Más de 4 años | Colombia - Sucre - Sincelejo | NA | NA | NA | NA | NA | NA | NA | Salud Total EPS | 21 | Entre 50 y 70 añps | Entre $700.000 y $999.999 | NA | Gobierno | gobierno | NA | NA | NA | SOLTERO | Estrato Dos | No | NA | NA | NA | Femenino | Entre $700.000 y $999.999 | NA | 1 | NA | NA | No tiene personas a cargo | Secundaria | NA | Secundaria | NA | Secundaria | 2 | NA | 5 o más | 2 | Estudiante | NA | Indigena | NA | No | No | Si | Diestro | NA | Si | NA | No | NA | NA | Otro | NA | NA | Otro | NA | No aplica | Empleado | NA | NA | Empleado | NA | No aplica | NA | NA | Si | No | No | Transporte | Arrendada | NA | NA | NA | INGENIERIA INDUSTRIAL | 4.433871 | 10 | 20192 | 63 | 1 | 0 | NA | NA | NA | NA | NA | NA | 0 |
| 19711 | SINCELEJO | JORNADA DIURNA | Pregrado | Presencial | Contado | alimentacion | NA | NA | Madre | Madre | De 1 a 2 años | NA | NA | Colombia - Sucre - Sincelejo | NA | NA | ninguna | NA | NA | Otro | NA | Coomeva EPS | 22 | Entre 31 y 49 años | Entre $100.000 y 699.999 | NA | NA | Gubernamental | NA | Discapacidad Fisica o motora | NA | SOLTERO | Estrato Dos | Si | NA | NA | NA | Masculino | Entre $100.000 y 699.999 | NA | 1 | NA | NA | No tiene personas a cargo | Universitario | NA | Universitario | NA | NA | 2 | NA | 4 | 1 | Estudiante | NA | Victima del conflicto | No | No | Si | Si | Zurdo | NA | Si | NA | No | NA | NA | Otro | NA | NA | NA | NA | No aplica | Empleado | NA | NA | NA | NA | No aplica | NA | Si | No | No | No | Transporte | Arrendada | NA | NA | NA | INGENIERIA DE SISTEMAS | 4.404546 | 10 | 20182 | 43 | 3 | 2 | 7 | 286700 | NA | NA | NA | NA | 0 |
| 10185 | SINCELEJO | JORNADA DIURNA | Pregrado | Presencial | NA | NA | NA | NA | NA | NA | NA | NA | NA | Colombia - Sucre - Since | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | NA | INGENIERIA DE SISTEMAS | 4.390000 | 10 | 20172 | 12 | 0 | 0 | NA | NA | NA | NA | NA | NA | 0 |
num_var=ncol(data)
data=data.frame(data)0.1 Limpieza de datos
data2=data[,-c(1:5)]
faltantes=apply(is.na(data2),2,sum)/1957*100
eliminan=which(faltantes>30)
data3=data2[,-c(eliminan)]
data3=data3[,-c(2,3)]
data3$v19=as.numeric(data3$v19)
names(data3)## [1] "v1" "v19"
## [3] "v20" "v21"
## [5] "v28" "v29"
## [7] "v30" "v34"
## [9] "v35" "v37"
## [11] "v40" "v43"
## [13] "v46" "v48"
## [15] "v49" "v50"
## [17] "v52" "v54"
## [19] "v56" "v57"
## [21] "v59" "v61"
## [23] "v69" "v78"
## [25] "v79" "v80"
## [27] "v81" "v82"
## [29] "NOMBRE.PROGRAMA" "PROMEDIO.GENERAL"
## [31] "ULTIMO.SEMESTRE.CURSADO" "MAXIMO.PERIODO.CURSADO"
## [33] "TOTAL.APROBADAS" "TOTAL.REPROBADAS"
## [35] "TOTAL.INCENTIVOS" "DESERTOR"table1(~.,data = data3)| Overall (N=1957) |
|
|---|---|
| v1 | |
| Beca Icetex | 240 (12.3%) |
| Beca o Auxilio de Bienestar Institucional | 37 (1.9%) |
| Beca o Auxilio de otro tipo | 48 (2.5%) |
| Contado | 384 (19.6%) |
| Crédito con CECAR | 84 (4.3%) |
| Crédito Icetex | 575 (29.4%) |
| Crédito otras entidades | 44 (2.2%) |
| Missing | 545 (27.8%) |
| v19 | |
| Mean (SD) | 24.0 (176) |
| Median [Min, Max] | 19.0 [1.00, 6890] |
| Missing | 441 (22.5%) |
| v20 | |
| Entre 20 y 30 años | 157 (8.0%) |
| Entre 31 y 49 años | 810 (41.4%) |
| Entre 50 y 70 añps | 521 (26.6%) |
| Más de 70 años | 31 (1.6%) |
| Missing | 438 (22.4%) |
| v21 | |
| $3.000.001 o más | 41 (2.1%) |
| Entre $1.000.000 y $1.599.999 | 240 (12.3%) |
| Entre $1.600.000 y $1.999.999 | 86 (4.4%) |
| Entre $100.000 y 699.999 | 715 (36.5%) |
| Entre $2.000.000 y $3.000.000 | 84 (4.3%) |
| Entre $700.000 y $999.999 | 353 (18.0%) |
| Missing | 438 (22.4%) |
| v28 | |
| CASADO | 19 (1.0%) |
| DIVORCIADO | 1 (0.1%) |
| OTRO | 34 (1.7%) |
| RELIGIOSOS | 1 (0.1%) |
| SEPARADO | 7 (0.4%) |
| SOLTERO | 1404 (71.7%) |
| UNION LIBRE | 45 (2.3%) |
| VIUDO | 3 (0.2%) |
| Missing | 443 (22.6%) |
| v29 | |
| Estrato cero | 41 (2.1%) |
| Estrato Cinco | 5 (0.3%) |
| Estrato Cuatro | 22 (1.1%) |
| Estrato Dos | 440 (22.5%) |
| Estrato Seis | 1 (0.1%) |
| Estrato Tres | 94 (4.8%) |
| Estrato Uno | 903 (46.1%) |
| No Aplica | 13 (0.7%) |
| Missing | 438 (22.4%) |
| v30 | |
| No | 917 (46.9%) |
| Si | 602 (30.8%) |
| Missing | 438 (22.4%) |
| v34 | |
| Femenino | 417 (21.3%) |
| Masculino | 1090 (55.7%) |
| No aplica | 7 (0.4%) |
| Missing | 443 (22.6%) |
| v35 | |
| $3.000.001 o más | 108 (5.5%) |
| Entre $1.000.000 y $1.599.999 | 335 (17.1%) |
| Entre $1.600.000 y $1.999.999 | 132 (6.7%) |
| Entre $100.000 y 699.999 | 469 (24.0%) |
| Entre $2.000.000 y $3.000.000 | 140 (7.2%) |
| Entre $700.000 y $999.999 | 335 (17.1%) |
| Missing | 438 (22.4%) |
| v37 | |
| 1 | 632 (32.3%) |
| 2 | 417 (21.3%) |
| 3 | 224 (11.4%) |
| 4 | 116 (5.9%) |
| 5 o más | 126 (6.4%) |
| Missing | 442 (22.6%) |
| v40 | |
| 1 | 286 (14.6%) |
| 2 | 443 (22.6%) |
| 3 | 64 (3.3%) |
| 4 o más | 43 (2.2%) |
| No tiene personas a cargo | 683 (34.9%) |
| Missing | 438 (22.4%) |
| v43 | |
| Ninguno | 101 (5.2%) |
| Posgrado | 143 (7.3%) |
| Primaria | 147 (7.5%) |
| Secundaria | 625 (31.9%) |
| Universitario | 503 (25.7%) |
| Missing | 438 (22.4%) |
| v46 | |
| 1 | 424 (21.7%) |
| 2 | 453 (23.1%) |
| 3 | 327 (16.7%) |
| 4 | 155 (7.9%) |
| 5 o más | 155 (7.9%) |
| Missing | 443 (22.6%) |
| v48 | |
| 1 | 20 (1.0%) |
| 2 | 61 (3.1%) |
| 3 | 199 (10.2%) |
| 4 | 518 (26.5%) |
| 5 o más | 721 (36.8%) |
| Missing | 438 (22.4%) |
| v49 | |
| 1 | 661 (33.8%) |
| 2 | 681 (34.8%) |
| 3 | 103 (5.3%) |
| 4 | 29 (1.5%) |
| 5 o más | 45 (2.3%) |
| Missing | 438 (22.4%) |
| v50 | |
| Ama (o) de casa | 18 (0.9%) |
| Empleado | 30 (1.5%) |
| Estudiante | 1433 (73.2%) |
| Independiente | 38 (1.9%) |
| Missing | 438 (22.4%) |
| v52 | |
| Afrodescendiente | 211 (10.8%) |
| Desplazado | 270 (13.8%) |
| Habitante de frontera | 10 (0.5%) |
| Indigena | 506 (25.9%) |
| LGTBI | 9 (0.5%) |
| Otros | 377 (19.3%) |
| ROM | 11 (0.6%) |
| Victima del conflicto | 126 (6.4%) |
| Missing | 437 (22.3%) |
| v54 | |
| No | 1193 (61.0%) |
| Si | 328 (16.8%) |
| Missing | 436 (22.3%) |
| v56 | |
| No | 194 (9.9%) |
| Si | 1325 (67.7%) |
| Missing | 438 (22.4%) |
| v57 | |
| Ambidiestro | 59 (3.0%) |
| Diestro | 1343 (68.6%) |
| Zurdo | 118 (6.0%) |
| Missing | 437 (22.3%) |
| v59 | |
| No | 471 (24.1%) |
| Si | 1048 (53.6%) |
| Missing | 438 (22.4%) |
| v61 | |
| No | 1498 (76.5%) |
| Si | 16 (0.8%) |
| Missing | 443 (22.6%) |
| v69 | |
| Está pensionado en el municipio donde tiene sus clases o tutorias presenciales | 251 (12.8%) |
| No aplica | 758 (38.7%) |
| Viaja cada vez que tiene programado clases o tutorias presenciales | 505 (25.8%) |
| Missing | 443 (22.6%) |
| v78 | |
| No | 503 (25.7%) |
| Si | 1017 (52.0%) |
| Missing | 437 (22.3%) |
| v79 | |
| No | 1450 (74.1%) |
| Si | 64 (3.3%) |
| Missing | 443 (22.6%) |
| v80 | |
| No | 1453 (74.2%) |
| Si | 67 (3.4%) |
| Missing | 437 (22.3%) |
| v81 | |
| Alimentación | 130 (6.6%) |
| Fotocopias | 40 (2.0%) |
| Materiales | 136 (6.9%) |
| Otra | 224 (11.4%) |
| Pensión | 246 (12.6%) |
| Transporte | 743 (38.0%) |
| Missing | 438 (22.4%) |
| v82 | |
| Arrendada | 289 (14.8%) |
| Familiar | 386 (19.7%) |
| Propia | 844 (43.1%) |
| Missing | 438 (22.4%) |
| NOMBRE.PROGRAMA | |
| INGENIERIA DE SISTEMAS | 754 (38.5%) |
| INGENIERIA INDUSTRIAL | 1203 (61.5%) |
| PROMEDIO.GENERAL | |
| Mean (SD) | 2.56 (1.04) |
| Median [Min, Max] | 2.87 [0, 4.97] |
| ULTIMO.SEMESTRE.CURSADO | |
| Mean (SD) | 6.17 (3.63) |
| Median [Min, Max] | 7.00 [1.00, 10.0] |
| Missing | 3 (0.2%) |
| MAXIMO.PERIODO.CURSADO | |
| Mean (SD) | 20200 (18.4) |
| Median [Min, Max] | 20200 [20200, 20200] |
| Missing | 3 (0.2%) |
| TOTAL.APROBADAS | |
| Mean (SD) | 36.7 (28.7) |
| Median [Min, Max] | 29.0 [0, 118] |
| TOTAL.REPROBADAS | |
| Mean (SD) | 12.2 (9.35) |
| Median [Min, Max] | 10.0 [0, 62.0] |
| TOTAL.INCENTIVOS | |
| Mean (SD) | 0.789 (1.76) |
| Median [Min, Max] | 0 [0, 10.0] |
| DESERTOR | |
| Mean (SD) | 0.240 (0.427) |
| Median [Min, Max] | 0 [0, 1.00] |
data4=na.omit(data3)
data4$v19=as.integer(data4$v19)
data4$DESERTOR[data4$DESERTOR == 1] ="Si"
data4$DESERTOR[data4$DESERTOR == 0] ="No"PUNTO #2: ANÁLISIS UNIVARIADO
Se utiliza la librería DataExplorer para visualizar rápidamente la estructuras de los datos:
library(DataExplorer)
plot_str(data4)
plot_str(data4, type = "r")introduce(data4)| rows | columns | discrete_columns | continuous_columns | all_missing_columns | total_missing_values | complete_rows | total_observations | memory_usage |
|---|---|---|---|---|---|---|---|---|
| 1390 | 36 | 29 | 7 | 0 | 0 | 1390 | 50040 | 410512 |
plot_intro(data4)
##Valores Faltantes
plot_missing(data4)
##Gráfica de barras
plot_bar(data4)
plot_histogram(data4)
PUNTO #3: ANÁLISIS BIVARIADO
1 Variables Cualitativas Vs Deserción
1.1 1) Estrato socioeconómico
table1(~v29|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| v29 | |||
| Estrato cero | 30 (2.8%) | 6 (1.8%) | 36 (2.6%) |
| Estrato Cinco | 2 (0.2%) | 3 (0.9%) | 5 (0.4%) |
| Estrato Cuatro | 17 (1.6%) | 5 (1.5%) | 22 (1.6%) |
| Estrato Dos | 308 (29.0%) | 85 (25.9%) | 393 (28.3%) |
| Estrato Seis | 1 (0.1%) | 0 (0%) | 1 (0.1%) |
| Estrato Tres | 72 (6.8%) | 15 (4.6%) | 87 (6.3%) |
| Estrato Uno | 621 (58.5%) | 214 (65.2%) | 835 (60.1%) |
| No Aplica | 11 (1.0%) | 0 (0%) | 11 (0.8%) |
ggplot(data4, aes(x=`v29`, fill = DESERTOR))+
geom_bar(position="fill", width=0.5, colour="red")+
labs(x="Estrato Socieconómico",y= "Proporción")+
theme_bw()+coord_flip()
1.2 2) Cómo paga sus estudios.
table1(~v21|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| v21 | |||
| $3.000.001 o más | 21 (2.0%) | 14 (4.3%) | 35 (2.5%) |
| Entre $1.000.000 y $1.599.999 | 172 (16.2%) | 50 (15.2%) | 222 (16.0%) |
| Entre $1.600.000 y $1.999.999 | 66 (6.2%) | 12 (3.7%) | 78 (5.6%) |
| Entre $100.000 y 699.999 | 500 (47.1%) | 156 (47.6%) | 656 (47.2%) |
| Entre $2.000.000 y $3.000.000 | 62 (5.8%) | 15 (4.6%) | 77 (5.5%) |
| Entre $700.000 y $999.999 | 241 (22.7%) | 81 (24.7%) | 322 (23.2%) |
ggplot(data4, aes(x=`v1`, fill = DESERTOR))+
geom_bar(position="fill", width=0.5, colour="red")+
labs(x="¿Cómo paga sus estudios?",y= "Proporción")+
theme_bw()+coord_flip()
1.3 3) Estado Civil
table1(~v28|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| v28 | |||
| CASADO | 11 (1.0%) | 6 (1.8%) | 17 (1.2%) |
| DIVORCIADO | 1 (0.1%) | 0 (0%) | 1 (0.1%) |
| OTRO | 25 (2.4%) | 7 (2.1%) | 32 (2.3%) |
| RELIGIOSOS | 1 (0.1%) | 0 (0%) | 1 (0.1%) |
| SEPARADO | 4 (0.4%) | 3 (0.9%) | 7 (0.5%) |
| SOLTERO | 990 (93.2%) | 296 (90.2%) | 1286 (92.5%) |
| UNION LIBRE | 30 (2.8%) | 13 (4.0%) | 43 (3.1%) |
| VIUDO | 0 (0%) | 3 (0.9%) | 3 (0.2%) |
ggplot(data4, aes(x=`v28`, fill = DESERTOR))+
geom_bar(position="fill", width=0.5, colour="red")+
labs(x="Estado Civil",y= "Proporción")+
theme_bw()+coord_flip()
1.4 4) “Los Factores económicos motivaron el retiro”
table1(~v30|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| v30 | |||
| No | 641 (60.4%) | 195 (59.5%) | 836 (60.1%) |
| Si | 421 (39.6%) | 133 (40.5%) | 554 (39.9%) |
ggplot(data4, aes(x=`v30`, fill = DESERTOR))+
geom_bar(position="fill", width=0.5, colour="red")+
labs(x="Los Factores económicos motivaron el retiro",y= "Proporción")+
theme_bw()+coord_flip()
1.5 5) Nivel educativo de quien paga sus estudios
table1(~v43|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| v43 | |||
| Ninguno | 65 (6.1%) | 26 (7.9%) | 91 (6.5%) |
| Posgrado | 104 (9.8%) | 25 (7.6%) | 129 (9.3%) |
| Primaria | 97 (9.1%) | 42 (12.8%) | 139 (10.0%) |
| Secundaria | 427 (40.2%) | 147 (44.8%) | 574 (41.3%) |
| Universitario | 369 (34.7%) | 88 (26.8%) | 457 (32.9%) |
ggplot(data4, aes(x=`v43`, fill = DESERTOR))+
geom_bar(position="fill", width=0.5, colour="red")+
labs(x="Nivel educativo de quien paga sus estudios",y= "Proporción")+
theme_bw()+coord_flip()
1.6 6) Edad de quien paga sus estudios
table1(~v20|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| v20 | |||
| Entre 20 y 30 años | 105 (9.9%) | 35 (10.7%) | 140 (10.1%) |
| Entre 31 y 49 años | 560 (52.7%) | 182 (55.5%) | 742 (53.4%) |
| Entre 50 y 70 añps | 376 (35.4%) | 104 (31.7%) | 480 (34.5%) |
| Más de 70 años | 21 (2.0%) | 7 (2.1%) | 28 (2.0%) |
ggplot(data4, aes(x=`v20`, fill = DESERTOR))+
geom_bar(position="fill", width=0.5, colour="red")+
labs(x="Edad de quien paga sus estudios",y= "Proporción")+
theme_bw()+coord_flip()
1.7 7) Egresos mensuales del núcleo familiar
table1(~v21|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| v21 | |||
| $3.000.001 o más | 21 (2.0%) | 14 (4.3%) | 35 (2.5%) |
| Entre $1.000.000 y $1.599.999 | 172 (16.2%) | 50 (15.2%) | 222 (16.0%) |
| Entre $1.600.000 y $1.999.999 | 66 (6.2%) | 12 (3.7%) | 78 (5.6%) |
| Entre $100.000 y 699.999 | 500 (47.1%) | 156 (47.6%) | 656 (47.2%) |
| Entre $2.000.000 y $3.000.000 | 62 (5.8%) | 15 (4.6%) | 77 (5.5%) |
| Entre $700.000 y $999.999 | 241 (22.7%) | 81 (24.7%) | 322 (23.2%) |
ggplot(data4, aes(x=`v21`, fill = DESERTOR))+
geom_bar(position="fill", width=0.5, colour="red")+
labs(x="Egresos mensuales del núcleo familiar",y= "Proporción")+
theme_bw()+coord_flip()
1.8 8) Población a la que pertenece
table1(~v52|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| v52 | |||
| Afrodescendiente | 146 (13.7%) | 50 (15.2%) | 196 (14.1%) |
| Desplazado | 187 (17.6%) | 66 (20.1%) | 253 (18.2%) |
| Habitante de frontera | 7 (0.7%) | 1 (0.3%) | 8 (0.6%) |
| Indigena | 346 (32.6%) | 116 (35.4%) | 462 (33.2%) |
| LGTBI | 6 (0.6%) | 1 (0.3%) | 7 (0.5%) |
| Otros | 271 (25.5%) | 69 (21.0%) | 340 (24.5%) |
| ROM | 9 (0.8%) | 2 (0.6%) | 11 (0.8%) |
| Victima del conflicto | 90 (8.5%) | 23 (7.0%) | 113 (8.1%) |
ggplot(data4, aes(x=`v52`, fill = DESERTOR))+
geom_bar(position="fill", width=0.5, colour="red")+
labs(x="Población a la que pertenece",y= "Proporción")+
theme_bw()+coord_flip()
1.9 9) Ocupación
table1(~v50|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| v50 | |||
| Ama (o) de casa | 14 (1.3%) | 3 (0.9%) | 17 (1.2%) |
| Empleado | 18 (1.7%) | 11 (3.4%) | 29 (2.1%) |
| Estudiante | 1007 (94.8%) | 304 (92.7%) | 1311 (94.3%) |
| Independiente | 23 (2.2%) | 10 (3.0%) | 33 (2.4%) |
ggplot(data4, aes(x=`v50`, fill = DESERTOR))+
geom_bar(position="fill", width=0.5, colour="red")+
labs(x="Ocupación",y= "Proporción")+
theme_bw()+coord_flip()
1.10 10) Tipo de vivienda
table1(~v82|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| v82 | |||
| Arrendada | 188 (17.7%) | 68 (20.7%) | 256 (18.4%) |
| Familiar | 266 (25.0%) | 86 (26.2%) | 352 (25.3%) |
| Propia | 608 (57.3%) | 174 (53.0%) | 782 (56.3%) |
ggplot(data4, aes(x=`v82`, fill = DESERTOR))+
geom_bar(position="fill", width=0.5, colour="red")+
labs(x="Tipo de vivienda",y= "Proporción")+
theme_bw()+coord_flip()
1.11 Variables Cuantitativas Vs Deserción
1.12 1) Edad
eliminar=which(data4$v19==6887)
edad=data4[,-c(eliminar)]table1(~v19|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| v19 | |||
| Mean (SD) | 25.7 (211) | 19.8 (5.93) | 24.4 (184) |
| Median [Min, Max] | 18.0 [5.00, 6890] | 18.5 [15.0, 65.0] | 18.0 [5.00, 6890] |
barplot(table(edad$v19), xlab = "Edad", ylab = "frecuencias",
main = "Edades de los estudiantes")
1.13 2) Total Aprobadas
table1(~TOTAL.APROBADAS|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| TOTAL.APROBADAS | |||
| Mean (SD) | 47.2 (29.9) | 27.0 (23.9) | 42.5 (29.9) |
| Median [Min, Max] | 48.0 [0, 118] | 20.0 [0, 103] | 38.0 [0, 118] |
ggplot(data4,aes(x=DESERTOR,y=TOTAL.APROBADAS,fill=DESERTOR))+geom_boxplot()+
theme_bw()+coord_flip()
1.14 3) Promedio General
table1(~PROMEDIO.GENERAL|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| PROMEDIO.GENERAL | |||
| Mean (SD) | 2.66 (1.08) | 2.49 (1.00) | 2.62 (1.06) |
| Median [Min, Max] | 3.13 [0.0786, 4.45] | 2.87 [0.0583, 4.97] | 3.05 [0.0583, 4.97] |
ggplot(data4,aes(x=DESERTOR,y=PROMEDIO.GENERAL,fill=DESERTOR))+geom_boxplot()+
theme_bw()+coord_flip()
1.15 4) TOTAL REPROBADAS
table1(~TOTAL.REPROBADAS|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| TOTAL.REPROBADAS | |||
| Mean (SD) | 14.4 (9.88) | 12.7 (7.76) | 14.0 (9.45) |
| Median [Min, Max] | 12.0 [0, 62.0] | 11.0 [0, 41.0] | 11.0 [0, 62.0] |
ggplot(data4,aes(x=DESERTOR,y=TOTAL.REPROBADAS,fill=DESERTOR))+geom_boxplot()+
theme_bw()+coord_flip()
1.16 5) tOTAL INCENTIVOS
table1(~TOTAL.INCENTIVOS|DESERTOR,data4)| No (N=1062) |
Si (N=328) |
Overall (N=1390) |
|
|---|---|---|---|
| TOTAL.INCENTIVOS | |||
| Mean (SD) | 0.874 (1.91) | 0.595 (1.31) | 0.808 (1.79) |
| Median [Min, Max] | 0 [0, 10.0] | 0 [0, 8.00] | 0 [0, 10.0] |
ggplot(data4,aes(x=DESERTOR,y=TOTAL.INCENTIVOS,fill=DESERTOR))+geom_boxplot()+
theme_bw()+coord_flip()